Uyghur text localization in images with complex backgrounds is a challenging yet important task for many applications. Generally, Uyghur characters in images consist of strokes with uniform features, ...and they are distinct from backgrounds in color, intensity, and texture. Based on these differences, we propose a FASTroke keypoint extractor, which is fast and stroke-specific. Compared with the commonly used MSER detector, FASTroke produces less than twice the amount of components and recognizes at least 10% more characters. While the characters in a line usually have uniform features such as size, color, and stroke width, a component similarity based clustering is presented without component-level classification. It incurs no extra errors by incorporating a component-level classifier while the computing cost is drastically reduced. The experiments show that the proposed method can achieve the best performance on the UICBI-500 benchmark dataset.
•A conceptual framework based on PSR-SENCE model is established, revealing influencing factors covering natural, economic, and social pressure-state-response aspects.•Inner mechanism on urban flood ...resilience in China are explored with Fuzzy-DEMATEL method.•Factors in natural pressure, economic state, social and economic response are proved to be most critical and highly recommended for future urban flood resilience improvement in China.•Proper implications for improving urban flood resilience are discussed with key influencing paths.
Urban flood is one of the most frequent and deadly natural disasters in the world, seriously affecting urban sustainability and people's well-being in China. As the largest developing country in the world, China urgently needs to improve its urban flood resilience. Previous studies related to urban flood resilience are mostly focused on its assessment method and simulation. However, few studies directly aim to reveal the influencing factors of urban flood resilience and their inner relationships. In order to make a significant contribution to the long-term improvement of urban flood resilience in the context of global climate change and urbanization, it is crucial to explore the influencing mechanisms of urban flood resilience. This study aims to identify key influencing factors and their interactions on urban flood resilience in China. To this end, a conceptual framework based on Pressure-State-Response model and Social-Economic-Natural Complex Ecosystem theory (PSR-SENCE model) are established and 24 factors are identified within three dimensions. The relationships between the factors are tested using a fuzzy-DEMATEL method. The results reveal that factors in pressure and response dimensions have a greater impact on the whole system, while the factors in the state dimension are more influenced by the other two dimensions. The results identify 14 critical factors, with four detailed influence paths discussed among the different dimensions. Accordingly, the implications for improving urban flood resilience are discussed within the context of the key influencing paths. The study provides a theoretical basis and approach to directly explore how the factors influencing urban flood resilience and proposes specific impact paths and improvement implications.
In this paper, we focus on exploring effective methods for faster and accurate semantic segmentation. A common practice to improve the performance is to attain high-resolution feature maps with ...strong semantic representation. Two strategies are widely used: atrous convolutions and feature pyramid fusion, while both are either computationally intensive or ineffective. Inspired by the Optical Flow for motion alignment between adjacent video frames, we propose a Flow Alignment Module (FAM) to learn
Semantic Flow
between feature maps of adjacent levels and broadcast high-level features to high-resolution features effectively and efficiently. Furthermore, integrating our FAM to a standard feature pyramid structure exhibits superior performance over other real-time methods, even on lightweight backbone networks, such as ResNet-18 and DFNet. Then to further speed up the inference procedure, we also present a novel Gated Dual Flow Alignment Module to directly align high-resolution feature maps and low-resolution feature maps where we term the improved version network as SFNet-Lite. Extensive experiments are conducted on several challenging datasets, where results show the effectiveness of both SFNet and SFNet-Lite. In particular, when using Cityscapes test set, the SFNet-Lite series achieve 80.1 mIoU while running at 60 FPS using ResNet-18 backbone and 78.8 mIoU while running at 120 FPS using STDC backbone on RTX-3090. Moreover, we unify four challenging driving datasets (i.e., Cityscapes, Mapillary, IDD, and BDD) into one large dataset, which we named Unified Driving Segmentation (UDS) dataset. It contains diverse domain and style information. We benchmark several representative works on UDS. Both SFNet and SFNet-Lite still achieve the best speed and accuracy trade-off on UDS, which serves as a strong baseline in such a challenging setting. The code and models are publicly available at
https://github.com/lxtGH/SFSegNets
.
Objective: The aim of this study was to examine the status of emotional labor among nursing school students in the end-of-life (EOL) nursing practicum and to provide support for them. We also ...clarified how the individual characteristics (empathy and sense of coherence SOC) of nursing school students are related to emotional labor. Methods: A questionnaire was administered to third-year nursing school students after the EOL nursing practicum. Results: The total score on the Emotional Labor Inventory for Nurses (ELIN) was 96.2±12.7 (n=81), indicating that the factors influencing emotional labor were related to empathy and SOC. Furthermore, SOC was determined to be the factor that reduced various other emotional labor factors, such as "surface adjustment" and "suppressed expression." Conclusions: During the EOL care practicum, emotional labor among nursing school students was high. Moreover, high scores on empathy tended to influence nursing practice. However, low scores in the SOC suggested evidence of psychological burden and emotional suppression.
It was shown recently that carrier sense multiple access (CSMA)-like distributed algorithms can achieve the maximal throughput in wireless networks (and task processing networks) under certain ...assumptions. One important but idealized assumption is that the sensing time is negligible, so that there is no collision. In this paper, we study more practical CSMA-based scheduling algorithms with collisions. First, we provide a Markov chain model and give an explicit throughput formula that takes into account the cost of collisions and overhead. The formula has a simple form since the Markov chain is "almost" time-reversible. Second, we propose transmission-length control algorithms to approach throughput-optimality in this case. Sufficient conditions are given to ensure the convergence and stability of the proposed algorithms. Finally, we characterize the relationship between the CSMA parameters (such as the maximum packet lengths) and the achievable capacity region.
In Social–Economic–Natural Complex Ecosystem (SENCE) theory, regional metabolism is seen as an integral part of a complex network of interconnected natural, economic and societal subsystems. ...Analyzing regional metabolism within this network assists observers to understand the concept in a broader context. Some qualitative tools such as simple matrix operations have been adopted to explore such networks but related research is highly fragmented. Here the emphasis is put on a qualitative network model (QNM) that integrates the existing tools into a unified analytical framework. The tools in the QNM are organized into three levels: (1) dominance analysis focuses on how to measure the performance of each component of a network; (2) consistency analysis is used to test whether the interactions between network components are contradictory to the desired development direction for regional metabolism; and (3) sustainability analysis returns three sustainability benchmarks for regional metabolism. With the aid of these tools, QNM can comprehensively explore such networks from multiple perspectives. To test the QNM construct, we conducted a case study on the regional metabolism of bio-fuels from locally grown plant crops, a hotspot in regional environmental research. In the case study we screened key components for inconsistent variables, identified the relationships between components, and rated the sustainability of the regional bio-fuel metabolism system suggested by the model. This study demonstrated that our research approach can inform bio-fuel policy making. The QNM is helpful in the understanding of regional metabolism in the broader context of SENCE theory and may be used to improve regional environmental management and policy-making.
•Regional metabolism can be seen as a network of numerous interconnected factors.•A qualitative network model was developed to hierarchically explore the networks.•We conducted a case study on bio-fuels from crops with the aid of the model.•The model can help users understand regional metabolism through network thinking.
A protocol was designed for plasmid curing using a novel counter-selectable marker, named
, in
. The
marker consists of the archaeal pyrrolysyl-tRNA synthetase (PylRS) and its cognate tRNA (tRNA
) ...with modification, and incorporates an unnatural amino acid (Uaa),
-benzyloxycarbonyl-l-lysine (ZK), at a sense codon in ribosomally synthesized proteins, resulting in bacterial growth inhibition or killing. Plasmid curing is performed by exerting toxicity on
located on the target plasmid, and selecting only proliferative bacteria. All tested bacteria obtained using this protocol had lost the target plasmid (64/64), suggesting that plasmid curing was successful. Next, we attempted to exchange plasmids with the identical replication origin and an antibiotic resistance gene without plasmid curing using a modified protocol, assuming substitution of plasmids complementing genomic essential genes. All randomly selected bacteria after screening had only the substitute plasmid and no target plasmid (25/25), suggesting that plasmid exchange was also accomplished. Counter-selectable markers based on PylRS-tRNA
, such as
, may be scalable in application due to their independence from the host genotype, applicability to a wide range of species, and high tunability due to the freedom of choice of target codons and Uaa's to be incorporated.
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