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In recent years, the multimodal medical imaging assisted diagnosis and treatment technology has developed rapidly. In brain disease diagnosis, CT-SPECT, MRI-PET and MRI-SPECT fusion images are more favored by brain doctors because...
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In recent years, the multimodal medical imaging assisted diagnosis and treatment technology has developed rapidly. In brain disease diagnosis, CT-SPECT, MRI-PET and MRI-SPECT fusion images are more favored by brain doctors because they contain both soft tissue structure information and organ metabolism information. Most of the previous medical image fusion algorithms are the migration of other types of image fusion methods and such operations often lose the features of the medical image itself. This paper proposes a multimodal medical image fusion model based on the residual attention mechanism of the generative adversarial network. In the design of the generator, we construct the residual attention mechanism block and the concat detail texture block. After source images are concatenated to a matrix , the matrix is put into two blocks at the same time to extract information such as size, shape, spatial location and texture details. The obtained features are put into the merge block to reconstruct the image. The obtained reconstructed image and source images are respectively put into two discriminators for correction to obtain the final fused image. The model has been experimented on the images of three databases and achieved good fusion results. Qualitative and quantitative evaluations prove that the model is superior to other comparison algorithms in terms of image fusion quality and detail information retention.
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We examine the impact of home country democracy on corporate tax avoidance. Specifically, we investigate how two aspects of democracy (political freedom and electoral democracy) are associated with corporate tax avoidance, respect...
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We examine the impact of home country democracy on corporate tax avoidance. Specifically, we investigate how two aspects of democracy (political freedom and electoral democracy) are associated with corporate tax avoidance, respectively. Political freedom reduces tax avoidance, as public scrutiny increases financial transparency risk of tax avoidance and participation in political decision-making process raises willingness to pay taxes. Electoral democracy increases tax avoidance, as election increases tax system complexity which in turn increases tax avoidance. Furthermore, we find that corruption control and social stability strengthen the negative association between political freedom and tax avoidance. Corporate tax complexity as percentage of overall tax complexity strengthens the positive association between electoral democracy and tax avoidance. Additional tests show shareholder protection and being a common law country weaken the negative association between political freedom and tax avoidance, and strengthen the positive association between electoral democracy and tax avoidance. Robustness checks using colony history as instrumental variable confirm the results.
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More and more controlled polymerization methodologies have been developed in the last decades. However, great challenges still remain in chemoselective polymerizations for advanced polymer precision synthesis. Traditionally, polym...
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More and more controlled polymerization methodologies have been developed in the last decades. However, great challenges still remain in chemoselective polymerizations for advanced polymer precision synthesis. Traditionally, polymerizations in the presence of multifunctional initiators or monomers with more reactive groups suffer from ill-defined products, low efficiency and tedious synthetic steps. Meanwhile, chemoselective copolymerizations from a mixed monomer feedstock is a long-term goal for synthesis of block and multiblock copolymers. Based on the development of novel catalysis, microflow technology, and switchable strategy in the absence/presence of external-stimuli, significant progress has been achieved in chemoselective polymerizations. In this review, chemoselective homopolymerizations (multifunctional initiators and multifunctional monomers) and copolymerizations (mixed monomers and mixed mechanisms) are highlighted in order. The future challenges and opportunities are proposed with the aim to provide the insight into further development of chemoselective polymerizations and advanced polymer precision synthesis.& nbsp; (c) 2021 Elsevier B.V. All rights reserved.
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Today’s biomedical imaging technology has been able to present the morphological structure or functional metabolic information of organisms at different scale levels, such as organ, tissue, cell, molecule and gene. However, diffe...
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Today’s biomedical imaging technology has been able to present the morphological structure or functional metabolic information of organisms at different scale levels, such as organ, tissue, cell, molecule and gene. However, different imaging modes have different application scope, advantages and disadvantages. In order to improve the role of medical image in disease diagnosis, the fusion of biomedical image information at different imaging modes and scales has become an important research direction in medical image. Traditional medical image fusion methods are all designed to measure the activity level and fusion rules. They are lack of mining the context features of different modes of image, which leads to the obstruction of improving the quality of fused images. In this paper, an attention-multiscale network medical image fusion model based on contextual features is proposed. The model selects five backbone modules in the VGG-16 network to build encoders to obtain the contextual features of medical images. It builds the attention mechanism branch to complete the fusion of global contextual features and designs the residual multiscale detail processing branch to complete the fusion of local contextual features. Finally, it completes the cascade reconstruction of features by the decoder to obtain the fused image. Ten sets of images related to five diseases are selected from the AANLIB database to validate the VANet model. Structural images are derived from MR images with high resolution and functional images are derived from SPECT and PET images that are good at describing organ blood flow levels and tissue metabolism. Fusion experiments are performed on twelve fusion algorithms including the VANet model. The model selects eight metrics from different aspects to build a fusion quality evaluation system to complete the performance evaluation of the fused images. Friedman’s test and the post-hoc Nemenyi test are introduced to conduct professional statistical tests to demonstrate the superiority of VANet model. The VANet model completely captures and fuses the texture details and color information of the source images. From the fusion results, the metabolism and structural information of the model are well expressed and there is no interference of color information on the structure and texture; in terms of the objective evaluation system, the metric value of the VANet model is generally higher than that of other methods.; in terms of efficiency, the time consumption of the model is acceptable; in terms of scalability, the model is not affected by the input order of source images and can be extended to tri-modal fusion.
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Recombinant DNA technologies have enabled the development of transgenic animal models for use in studying a myriad of diseases and biological states. By placing fluorescent reporters under the direct regulation of the promoter reg...
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Recombinant DNA technologies have enabled the development of transgenic animal models for use in studying a myriad of diseases and biological states. By placing fluorescent reporters under the direct regulation of the promoter region of specific marker proteins, these models can localize and characterize very specific cell types. One important application of transgenic species is the study of the cytoarchitecture of the nervous system. Neurofluorescent reporters can be used to study the structural patterns of nerves in the central or peripheral nervous system in vivo, as well as phenomena involving embryologic or adult neurogenesis, injury, degeneration, and recovery. Furthermore, crucial molecular factors can also be screened via the transgenic approach, which may eventually play a major role in the development of therapeutic strategies against diseases like Alzheimer's or Parkinson's. This review describes currently available reporters and their uses in the literature as well as potential neural markers that can be leveraged to create additional, robust transgenic models for future studies.
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Among the methods of hand function rehabilitation after stroke, robot-assisted rehabilitation is widely used, and the use of hand rehabilitation robots can provide functional training of the hand or assist the paralyzed hand with ...
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Among the methods of hand function rehabilitation after stroke, robot-assisted rehabilitation is widely used, and the use of hand rehabilitation robots can provide functional training of the hand or assist the paralyzed hand with activities of daily living. However, patients with hand disorders consistently report that the needs of some users are not being met. The purpose of this review is to understand the reasons why these user needs are not being adequately addressed, to explore research on hand rehabilitation robots, to review their current state of research in recent years, and to summarize future trends in the hope that it will be useful to researchers in this research area. This review summarizes the techniques in this paper in a systematic way. We first provide a comprehensive review of research institutions, commercial products, and literature. Thus, the state of the art and deficiencies of functional hand rehabilitation robots are sought and guide the development of subsequent hand rehabilitation robots. This review focuses specifically on the actuation and control of hand functional rehabilitation robots, as user needs are primarily focused on actuation and control strategies. We also review hand detection technologies and compare them with patient needs. The results show that the trends in recent years are more inclined to pursue new lightweight materials to improve hand adaptability, investigating intelligent control methods for human-robot interaction in hand functional rehabilitation robots to improve control robustness and accuracy, and VR virtual task positioning to improve the effectiveness of active rehabilitation training.
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The ecological risk assessment of land ecosystems plays a vital role in land environment protection and management in China. To identify the ecological impairment in land ecosystems, risk assessment of regional land ecology was co...
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The ecological risk assessment of land ecosystems plays a vital role in land environment protection and management in China. To identify the ecological impairment in land ecosystems, risk assessment of regional land ecology was conducted in Daye, a traditional mining city in Central China, using the relative risk model (RRM). The study area was divided into six sub-regions; and the sources, stressors, habitats, and end points of the impairment were identified. A conceptual model was built to represent the ecological interactions among risk components. Results showed the following: (1) The traditional iron-coal mining sub-region and the mineral processing sub-region exhibited high risk. (2) Mining was the largest risk source, followed by solid waste piling and urbanization. (3) Disappearance of habitats was the greatest risk stressor, followed by the accumulation of pollutants and heavy metals. (4) Among the eight identified habitats, the lake habitat was the most likely to be affected. (5) Health threats, soil contamination, and landscape aesthetic dysfunctions appeared to be the end points under the largest risk pressure. Finally, Monte Carlo analysis was used to evaluate the effects of uncertainty on risk model predictions. Our assessment model was proven to be generally valid for regional land ecology risk assessment.
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Acetylcholinesterase inhibitors (AChEIs) are an attractive research subject owing to their potential applications in the treatment of neurodegenerative diseases. Fungi and bacteria are major producers of AChEIs. Their active ingre...
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Acetylcholinesterase inhibitors (AChEIs) are an attractive research subject owing to their potential applications in the treatment of neurodegenerative diseases. Fungi and bacteria are major producers of AChEIs. Their active ingredients of fermentation products include alkaloids, terpenoids, phenylpropanoids, and steroids. A variety of in vitro acetylcholinesterase inhibitor assays have been developed and used to measure the activity of acetylcholinesterases, including modified Ellman's method, thin layer chromatography bioautography, and the combined liquid chromatography-mass spectrometry/modified Ellman's method. In this review, we provide an overview of the different detection methodologies, the microbe-derived AChEIs, and their producing strains.
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Airborne laser bathymetry (ALB) is employed to measure shallow depth water by using a high sampling rate and point density. Thus, the problems of using traditional detection methods in inaccessible areas can be avoided. This study...
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Airborne laser bathymetry (ALB) is employed to measure shallow depth water by using a high sampling rate and point density. Thus, the problems of using traditional detection methods in inaccessible areas can be avoided. This study focuses on practical solutions for receiving echo signals, identifying target echoes, and integrating land and underwater terrain point cloud data in coastal environments. Optimization of the system design and its data processing scheme is undertaken to improve the performance of the receiving system based on a single-band ALB system developed by the authors at Shenzhen University. A flight experiment over eastern Hainan Island was conducted, during which the effectiveness of the proposed strategy was verified. Finally, the technical characteristics of the self-developed system are summarized to provide a reliable reference source for the subsequent industrialization and production of related marine light detection and ranging (LiDAR) laser systems.
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To realize project management improvement, many different objectives have to be considered simultaneously due to the nature of complexity and uncertainty in construction projects. Along with the rapid development of progressive te...
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To realize project management improvement, many different objectives have to be considered simultaneously due to the nature of complexity and uncertainty in construction projects. Along with the rapid development of progressive technologies, solving the project management problem from the multi-objective optimization (MOO) perspective has drawn a lot of attention and become a necessary trend. To better promote the adoption of MOO for solving problems in the construction industry, the paper presents a systematic review under both scientometric and qualitative analysis to understand the current state and discusses the future research trends of MOO for project improvement. To begin with, a scientometric review is performed to explore the characteristics of keywords, journals, and clusters based on 411 journal articles published in 1991-2020. It is found that there has been an explosion of MOO-related papers, especially in the past 10 years. Then, a brief understanding of MOO is provided, which analyses the key problems in the adoption of MOO for project improvement management. Special concerns have been put on six hot research topics, where the MOO methods have been widely applied for achieving better project performance, including (1) project planning and constructability, (2) prefabrication and supply chain, (3) workplace safety and risk management, (4) construction automation and digitalization, (5) structural health monitoring, and (6) emergency response and evacuation management. Based on the systematic review, challenges of promoting wide adoption of MOO for better project improvement are identified, i.e., incompatibility with dynamic features, ambiguity of input-output relationship, and low interaction in the advance project management. To address these challenges, three potential directions, adaptive optimization, interpretable mapping and interactive optimization, are discussed.
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