An urgent need for early detection and diagnosis of diseases continuously pushes the advancements of imaging modalities and contrast agents. Current challenges remain for fast and detailed imaging of ...tissue microstructures and lesion characterization that could be achieved via development of nontoxic contrast agents with longer circulation time. Nanoparticle technology offers this possibility. Here, we review nanoparticle-based contrast agents employed in most common biomedical imaging modalities, including fluorescence imaging, MRI, CT, US, PET and SPECT, addressing their structure related features, advantages and limitations. Furthermore, their applications in each imaging modality are also reviewed using commonly studied examples. Future research will investigate multifunctional nanoplatforms to address safety, efficacy and theranostic capabilities. Nanoparticles as imaging contrast agents have promise to greatly benefit clinical practice.
Abstract
ERA5 is the latest fifth-generation reanalysis global atmosphere dataset from the European Centre for Medium-Range Weather Forecasts, replacing ERA-Interim as the next generation of ...representative satellite-observational data on the global scale. ERA5 data have been evaluated and applied in different regions, but the performances are inconsistent. Meanwhile, there are few precise evaluations of ERA5 precipitation data over long time series have been performed in Chinese mainland. This study evaluates the temporal-spatial performance of ERA5 precipitation data from 1979 to 2018 based on gridded-ground meteorological station observational data across China. The results showed that ERA5 data could capture the annual and seasonal patterns of observed precipitation in China well, with correlation coefficient values ranging from 0.796 to 0.945, but ERA5 slightly overestimated precipitation in the summer. Nonetheless, the results also showed that the accuracy of the precipitation products was strongly correlated with topographic distribution and climatic divisions. The performance of ERA5 shows spatial inherently across China that the highest correlation coefficient values locate in eastern, Northwestern and North China and the lowest biases locate in Southeast China. This study provides a reliable data assessment of the ERA5 data and precipitation trend analyses in China. The results provide accuracy references for the further use of precipitation satellite data for hydrological calculations and climate numerical simulations.
The remarkable regeneration capability of plant tissues or organs under culture conditions has underlain an extensive practice for decades. The initial step in plant in vitro regeneration often ...involves the induction of a pluripotent cell mass termed callus, which is driven by the phytohormone auxin and occurs via a root development pathway. However, the key molecules governing callus formation remain unknown. Here we demonstrate that Arabidopsis LATERAL ORGAN BOUNDARIES DOMAIN （LBD）/ASYMMETRIC LEAVES2-LIKE （ASL） transcription factors are involved in the control of callus formation program. The four LBD genes downstream of AUXIN RESPONSE FACTORs （ARFs）, LBD16, LBD17, LBD18 and LBD29, are rapidly and dramatically induced by callus-inducing medium （CIM） in multiple organs. Ectopic expression of each of the four LBD genes in Arabidopsis is sufficient to trigger spontaneous callus formation without exogenous phytohormones, whereas suppression of LBD function inhibits the callus formation induced by CIM. Moreover, the callus triggered by LBD resembles that induced by CIM by characteristics of ectopically activated root meristem genes and efficient regeneration capacity. These findings define LBD transcription factors as key regulators in the callus induction process, thereby establishing a molecular link between auxin signaling and the plant regeneration program.
Actin and spectrin play important roles in neurons, but their organization in axons and dendrites remains unclear. We used stochastic optical reconstruction microscopy to study the organization of ...actin, spectrin, and associated proteins in neurons. Actin formed ringlike structures that wrapped around the circumference of axons and were evenly spaced along axonal shafts with a periodicity of ∼180 to 190 nanometers. This periodic structure was not observed in dendrites, which instead contained long actin filaments running along dendritic shafts. Adducin, an actin-capping protein, colocalized with the actin rings. Spectrin exhibited periodic structures alternating with those of actin and adducin, and the distance between adjacent actin-adducin rings was comparable to the length of a spectrin tetramer. Sodium channels in axons were distributed in a periodic pattern coordinated with the underlying actin-spectrin—based cytoskeleton.
In this review paper, we reviewed heavy metal ions removal using MOF-based micro/nanoscaled materials. Designs and synthesis of bulk MOFs and MOFs based composite materials with high adsorption ...efficiency-oriented specific structure modulations and/or functionalization was summarized and discussed. The adsorption capacities and mechanisms towards diverse heavy metal ions were elaborated. The content in this paper would help researchers to deeply understand interactions between MOFs with different structures and heavy metal ions, as well as strategies for design and synthesis of MOF based micro/nano-materials as high-performance adsorbents for environmental remediation.
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•MOF-based micro/nanoscaled materials display excellent adsorption performance.•Review of MOF-based micro/nanoscaled materials for heavy metal ions removal.•High efficiency-oriented synthesis of MOF-based micro/nanoscaled materials.•Heavy metal ions adsorption ability of MOF-based micro/nanoscaled materials.
The rapid industrial and agricultural expansion is arousing increasingly severe heavy metal ion pollution due to their high toxicity to human beings and detrimental effect on the environment and ecology. Therefore, heavy metal ion removal from wastewater is an urgent need which has become an important area of research in both academia and industry. Advanced material has been synthesized either to overhaul classical water purification methods or bring avant-garde system to overcome the challenges, such as improving cost efficiency, scalability, multiple metals removal, reusability etc. Metal-organic frameworks (MOFs), a new kind of three-dimensional organic–inorganic complex, have attracted incredible attention to satisfy these challenges, especially in the field of adsorption. This is due to their highly porous structure, extremely high surface area, and highly available exposed adsorptive sites. Remarkable progress has been done in this sector which urges a comprehensive, but critical review which could be substantial and easily readable. Here, we aimed to cover these cutting-edge research developments on design, synthesis, and applications of MOFs in effective heavy metals removal from water. We focused on high adsorption efficiency-oriented design and synthesis of MOF-based micro/nanoscaled materials including bulk MOF-based micro/nano materials (bulk MOFs, composites, and MOFs with unique nanostructures), two-dimensional (2D) MOF nanosheets, and three-dimensional (3D) MOFs incorporated porous membranes. The engineering principles of these structures for pollutants removal were corroborated and their performances were thoroughly compared. Based on our analysis and discussions, the most desirable characters of high-efficiency MOFs based adsorbents were revealed. We also scrutinized the knowledge gaps and gave future directions and perspectives for new experimental design. This review paper could provide some references and directions on the specific MOFs fabrication towards efficient heavy metal ions removal.
•Relevant studies of gas production from natural gas hydrate are reviewed.•The limitations, challenges and some questions of NGH are discussed.•NGH exploitation are mainly carried out from numerical ...simulation, experiments and field tests.•Characteristics of the flow, heat and mass transfer are still not comprehensively recognized.•Environmental impacts and economics are still unclear and await further research.
Natural gas hydrates (NGHs), which extensively exist in sea-floor and permafrost regions, are considered as an alternative energy in the future for the fossil fuels approaching depletion with the gradually increasing energy consumption. Because of the particularity of NGH stabilizing only in the conditions of the high pressure and the low temperature, the exploitation of NGH is distinguished from those of petroleum and natural gas. Researchers over the world are devoting themselves to developing the technologies of NGH exploitation. However, till now, few NGH exploitation technology is identified and employed to exploit commercially NGH. Although there do be two cases of short-term NGH exploitation in Mackenzie Delta (CAN), Alaska North Slope (USA) and Nankai Trough (JAP) in the past 10years. It is mainly because some characteristics of the flow (gas, water, gas-hydrate slurry, quicksand, etc.), the issues of heat and mass transfer, the risk assessment and the economic evaluation are still not comprehensively recognized. Presently, the researches of NGH exploitation are mainly carried out from three aspects, numerical simulation and analysis, experimental simulation and field trial exploitation for the different technologies. In this paper, we comprehensively review the relevant studies of NGHs and propose our comments. We not only represent the achievements for the NGH exploitation researches, but also discuss the limitations and challenges, raise some questions and put forward some suggestions from our points of view.
Contemporarily, quantitative finance and multi-factor stock selection have begun to develop in China. Meanwhile, the new coronavirus from 2020 has brought a huge impact on the market, so it is very ...important to explore the effectiveness of multi-factor stock selection model during the period. In this study, stocks in the medical industry are selected as the research object, and price-earnings ratio, total market value and market sales ratio are selected as the research indicators. In this study, RiceQuant quantitative trading platform was used to conduct backtesting during the epidemic period, and the effectiveness of stock selection indicators during the epidemic period was analysed through data results. The results showed that under the epidemic situation, changing the P/E ratio, total market value and price-to-sales ratio had an impact on the earnings of stock selection portfolio, which proved that the P/E ratio, total market value and price-to-sales ratio were all effective indicators. These results prove the effectiveness of multi-factor stock selection model under the COVID-19, and list the effective stock selection factors under the epidemic situation. It can provide an in-depth understanding of the impact of the epidemic on the market and enrich the study of multi-factor stock selection model.
Atroposelective arene formation is an efficient method to build axially chiral molecules with multi‐substituted arenes. Reported here is an organocatalyzed atroposelective arene formation reaction by ...an N‐heterocyclic carbene (NHC) catalyzed formal 4+2 cycloaddition of conjugated dienals and α‐aryl ketones. This study expands the synthetic potential of NHC organocatalysis and provides a competitive pathway for the synthesis of axially chiral ligands, catalysts, and other functional molecules.
Atroposelective 4+2: A new organocatalyzed atroposelective arene formation reaction involves a carbene‐catalyzed formal 4+2 cycloaddition of conjugated enals and α‐aryl ketones. This study expands the synthetic potential of N‐heterocyclic carbene (NHC) organocatalysis and provides a competitive pathway for the synthesis of axially chiral ligands, catalysts, and other functional molecules.
•A semi-supervised learning method named CAE-SGAN is proposed to classify surface defects of steels.•CAE-SGAN improves the performance of SGAN with limited training samples.•When training the ...discriminator of SGAN, the decoder network of CAE is not truncated.•CAE-SGAN is tested with sample images collected from three different steel production lines.•CAE-SGAN provides a better way to apply deep learning methods to some industrial scenes.
Defect inspection is extremely crucial to ensure the quality of steel surface. It affects not only the subsequent production, but also the quality of the end-products. However, due to the rare occurrence and appearance variations of defects, surface defect identification of steels has always been a challenging task. Recently, deep learning methods have shown outstanding performance in image classification, especially when there are enough training samples. Since most sample images of steel surface are unlabeled, a new semi-supervised learning method is proposed to classify surface defects of steels. The new method is named CAE-SGAN, as it is based on Convolutional Autoencoder (CAE) and semi-supervised Generative Adversarial Networks (SGAN). CAE-SGAN first trains a stacked CAE through massive unlabeled data. Considering the appearance variations of defects, the passthrough layer is used to help CAE extract fine-grained features. After CAE is trained, the encoder network of CAE is reserved as the feature extractor and fed into a softmax layer to form a new classifier. SGAN is introduced for semi-supervised learning to further improve the generalization ability of the new method. The classifier is trained with images collected from real production lines and images randomly generated by SGAN. Extensive experiments are carried out with samples captured from different steel production lines, and the results indicate that CAE-SGAN had yielded best performances compared with traditional methods. Especially for hot rolled plates, the classification rate is improved by around 16%.
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