Interaction Mechanism of the Germination Stimulants Karrikins and Their Receptor ShKAI2iB

2020 ◽  
Vol 124 (44) ◽  
pp. 9812-9819
Author(s):  
Ji-Long Zhang ◽  
Xiaoting Liu ◽  
Hong-Xing Zhang
Keyword(s):  
Interaction Mechanism ◽  
Germination Stimulants

scholarly journals Interaction mechanism of aloe-emodin with trypsin: molecular structure–affinity relationship and effect on biological activities

RSC Advances ◽  
2020 ◽  
Vol 10 (35) ◽  
pp. 20862-20871
Author(s):  
Guoyan Ren ◽  
He Sun ◽  
Gen Li ◽  
Jinling Fan ◽  
Lin Du ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Biological Activity ◽  
Biological Activities ◽  
Interaction Mechanism ◽  
Mechanism Of Interaction ◽  
Development And Utilization ◽  
Aloe Emodin

The mechanism of interaction between AE and trypsin was studied firstly. The biological activity of both decreased after the interaction. These results provide a basis for the development and utilization of AE.

scholarly journals Modulation of Macrophages M1/M2 Polarization Using Carbohydrate-Functionalized Polymeric Nanoparticles

Polymers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 88
Author(s):  
Raquel G. D. Andrade ◽  
Bruno Reis ◽  
Benjamin Costas ◽  
Sofia A. Costa Lima ◽  
Salette Reis
Keyword(s):  
Inflammatory Responses ◽  
Polymeric Nanoparticles ◽  
Interaction Mechanism ◽  
Mannose Receptor ◽  
The Body ◽  
Receptor Expression ◽  
Production Methods ◽  
Polymeric Nanocarriers ◽  
Efficient Delivery

Exploiting surface endocytosis receptors using carbohydrate-conjugated nanocarriers brings outstanding approaches to an efficient delivery towards a specific target. Macrophages are cells of innate immunity found throughout the body. Plasticity of macrophages is evidenced by alterations in phenotypic polarization in response to stimuli, and is associated with changes in effector molecules, receptor expression, and cytokine profile. M1-polarized macrophages are involved in pro-inflammatory responses while M2 macrophages are capable of anti-inflammatory response and tissue repair. Modulation of macrophages’ activation state is an effective approach for several disease therapies, mediated by carbohydrate-coated nanocarriers. In this review, polymeric nanocarriers targeting macrophages are described in terms of production methods and conjugation strategies, highlighting the role of mannose receptor in the polarization of macrophages, and targeting approaches for infectious diseases, cancer immunotherapy, and prevention. Translation of this nanomedicine approach still requires further elucidation of the interaction mechanism between nanocarriers and macrophages towards clinical applications.

Graphene-based materials for adsorptive removal of pollutants from water and underlying interaction mechanism

2021 ◽  
Vol 289 ◽  
pp. 102360
Author(s):  
Jingyi Wang ◽  
Jiawen Zhang ◽  
Linbo Han ◽  
Jianmei Wang ◽  
Liping Zhu ◽  
...  
Keyword(s):  
Interaction Mechanism ◽  
Adsorptive Removal

Time-Efficient Ensemble Learning with Sample Exchange for Edge Computing

2021 ◽  
Vol 21 (3) ◽  
pp. 1-17
Author(s):  
Wu Chen ◽  
Yong Yu ◽  
Keke Gai ◽  
Jiamou Liu ◽  
Kim-Kwang Raymond Choo
Keyword(s):  
Ensemble Learning ◽  
Real World ◽  
Interaction Mechanism ◽  
Training Model ◽  
Edge Computing ◽  
Learning Techniques ◽  
Multi Agent ◽  
Real World Datasets ◽  
Entire Dataset ◽  
Exchange Data

In existing ensemble learning algorithms (e.g., random forest), each base learner’s model needs the entire dataset for sampling and training. However, this may not be practical in many real-world applications, and it incurs additional computational costs. To achieve better efficiency, we propose a decentralized framework: Multi-Agent Ensemble. The framework leverages edge computing to facilitate ensemble learning techniques by focusing on the balancing of access restrictions (small sub-dataset) and accuracy enhancement. Specifically, network edge nodes (learners) are utilized to model classifications and predictions in our framework. Data is then distributed to multiple base learners who exchange data via an interaction mechanism to achieve improved prediction. The proposed approach relies on a training model rather than conventional centralized learning. Findings from the experimental evaluations using 20 real-world datasets suggest that Multi-Agent Ensemble outperforms other ensemble approaches in terms of accuracy even though the base learners require fewer samples (i.e., significant reduction in computation costs).

scholarly journals Spatial Distribution and Land Use of Traditional Villages in Southwest China

2021 ◽  
Vol 13 (11) ◽  
pp. 6326
Author(s):  
Xiye Zheng ◽  
Jiahui Wu ◽  
Hongbing Deng
Keyword(s):  
Cultural Heritage ◽  
Influencing Factors ◽  
Landscape Pattern ◽  
Southwest China ◽  
Spatial Clustering ◽  
Interaction Mechanism ◽  
Cultivated Land ◽  
River Population ◽  
Local Conditions ◽  
Countermeasures And Suggestions

Traditional villages are the historical and cultural heritage of people around the world. With the increases in urbanization and industrialization, the continuation of traditional villages and the inheritance of historical and cultural heritage are facing risk. Therefore, to grasp the spatial characteristics of them and the human–nature interaction mechanism in Southwest China, we analyzed the distribution pattern of traditional villages using the ArcGIS software. Then, we further analyzed the spatial clustering characteristics, influencing factors and landscape pattern, and put forward relevant protection countermeasures and suggestions. The results revealed that traditional villages in Southwest China were clustered, being mainly distributed in areas with relatively low elevation, gentle slopes, low relative positions, nearby water sources, and convenient transportation. They can be divided into four categories due to obvious differences in influencing factors such as elevation, slope, relative position, distance to the nearest river, population density, etc. The landscape pattern of traditional villages differed among the different clusters, being mainly composed of forests, shrubs, and cultivated land. With the increase in the buffer radius, the landscape pattern of them changed significantly. The results of this study reflect that traditional villages and the natural environment are interdependent, so the protection of traditional villages should carry out measures according to local conditions.

Near-Tip Residual Stress as an Independent Load Interaction Mechanism

2021 ◽  
pp. 106364
Author(s):  
R. Sunder ◽  
Devaraj Raut ◽  
Vikram Jayaram ◽  
Praveen Kumar ◽  
Vijayendra Shastri
Keyword(s):  
Residual Stress ◽  
Interaction Mechanism

Acoustic-based Upper Facial Action Recognition for Smart Eyewear

2021 ◽  
Vol 5 (2) ◽  
pp. 1-28
Author(s):  
Wentao Xie ◽  
Qian Zhang ◽  
Jin Zhang
Keyword(s):  
Frequency Domain ◽  
Orthogonal Frequency Division Multiplexing ◽  
Interaction Mechanism ◽  
Phase Changes ◽  
Experimental Result ◽  
Selective Fading ◽  
Time Frequency ◽  
Facial Action ◽  
Frequency Selective Fading ◽  
Frequency Selective

Smart eyewear (e.g., AR glasses) is considered to be the next big breakthrough for wearable devices. The interaction of state-of-the-art smart eyewear mostly relies on the touchpad which is obtrusive and not user-friendly. In this work, we propose a novel acoustic-based upper facial action (UFA) recognition system that serves as a hands-free interaction mechanism for smart eyewear. The proposed system is a glass-mounted acoustic sensing system with several pairs of commercial speakers and microphones to sense UFAs. There are two main challenges in designing the system. The first challenge is that the system is in a severe multipath environment and the received signal could have large attenuation due to the frequency-selective fading which will degrade the system's performance. To overcome this challenge, we design an Orthogonal Frequency Division Multiplexing (OFDM)-based channel state information (CSI) estimation scheme that is able to measure the phase changes caused by a facial action while mitigating the frequency-selective fading. The second challenge is that because the skin deformation caused by a facial action is tiny, the received signal has very small variations. Thus, it is hard to derive useful information directly from the received signal. To resolve this challenge, we apply a time-frequency analysis to derive the time-frequency domain signal from the CSI. We show that the derived time-frequency domain signal contains distinct patterns for different UFAs. Furthermore, we design a Convolutional Neural Network (CNN) to extract high-level features from the time-frequency patterns and classify the features into six UFAs, namely, cheek-raiser, brow-raiser, brow-lower, wink, blink and neutral. We evaluate the performance of our system through experiments on data collected from 26 subjects. The experimental result shows that our system can recognize the six UFAs with an average F1-score of 0.92.

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