scale transition
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Author(s):  
Deepanwita Banerjee ◽  
Thomas Eng ◽  
Yusuke Sasaki ◽  
Aparajitha Srinivasan ◽  
Asun Oka ◽  
...  

Corynebacterium glutamicum is an ideal microbial chassis for production of valuable bioproducts including amino acids and next generation biofuels. Here we resequence engineered isopentenol (IP) producing C. glutamicum BRC-JBEI 1.1.2 strain and assess differential transcriptional profiles using RNA sequencing under industrially relevant conditions including scale transition and compare the presence vs absence of an ionic liquid, cholinium lysinate ([Ch][Lys]). Analysis of the scale transition from shake flask to bioreactor with transcriptomics identified a distinct pattern of metabolic and regulatory responses needed for growth in this industrial format. These differential changes in gene expression corroborate altered accumulation of organic acids and bioproducts, including succinate, acetate, and acetoin that occur when cells are grown in the presence of 50 mM [Ch][Lys] in the stirred-tank reactor. This new genome assembly and differential expression analysis of cells grown in a stirred tank bioreactor clarify the cell response of an C. glutamicum strain engineered to produce IP.


2021 ◽  
Author(s):  
Deepanwita Banerjee ◽  
Thomas Eng ◽  
Yusuke Sasaki ◽  
Aparajitha Srinivasan ◽  
Asun Oka ◽  
...  

AbstractCorynebacterium glutamicum is an ideal microbial chassis for the production of valuable bioproducts including amino acids and next-generation biofuels. Here we resequence engineered isopentenol (IP) producing C. glutamicum BRC-JBEI 1.1.2 strain and assess differential transcriptional profiles using RNA sequencing under industrially relevant conditions including scale transition and compare the presence vs. absence of an ionic liquid, cholinium lysinate ([Ch][Lys]). Analysis of the scale transition from shake flask to bioreactor with transcriptomics identified a distinct pattern of metabolic and regulatory responses needed for growth in this industrial format. These differential changes in gene expression corroborate altered accumulation of organic acids and bioproducts, including succinate, acetate, and acetoin that occur when cells are grown in the presence of 50mM [Ch][Lys] in the stirred-tank reactor. This new genome assembly and differential expression analysis of cells grown in a stirred tank bioreactor clarify the cell response of a C. glutamicum strain engineered to produce IP.


Author(s):  
Ziyu Jia ◽  
Youfang Lin ◽  
Jing Wang ◽  
Xuehui Wang ◽  
Peiyi Xie ◽  
...  

Sleep staging is fundamental for sleep assessment and disease diagnosis. Although previous attempts to classify sleep stages have achieved high classification performance, several challenges remain open: 1) How to effectively extract salient waves in multimodal sleep data; 2) How to capture the multi-scale transition rules among sleep stages; 3) How to adaptively seize the key role of specific modality for sleep staging. To address these challenges, we propose SalientSleepNet, a multimodal salient wave detection network for sleep staging. Specifically, SalientSleepNet is a temporal fully convolutional network based on the $U^2$-Net architecture that is originally proposed for salient object detection in computer vision. It is mainly composed of two independent $U^2$-like streams to extract the salient features from multimodal data, respectively. Meanwhile, the multi-scale extraction module is designed to capture multi-scale transition rules among sleep stages. Besides, the multimodal attention module is proposed to adaptively capture valuable information from multimodal data for the specific sleep stage. Experiments on the two datasets demonstrate that SalientSleepNet outperforms the state-of-the-art baselines. It is worth noting that this model has the least amount of parameters compared with the existing deep neural network models.


Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 647
Author(s):  
Yanbo Qu ◽  
Xiaozhen Dong ◽  
Lingyun Zhan ◽  
Hongyun Si ◽  
Zongli Ping ◽  
...  

In order to enhance the scientific understanding of the transition law of rural residential areas and enrich the theory and method system of land use transition research, this article takes Shandong Province as an example and constructs a comprehensive research framework of rural residential land scale, structure, and function from the perspective of the combination of the macro and micro scales based on differences between the rural residential areas in the region and the village scale forms. Using model quantitative analysis and horizontal comparative analysis methods, this paper explores the process characteristics of rural residential land use scale transition and the corresponding stage differentiation law of spatial structure and system function. Research has shown that the stage characteristics of the scale transition of rural residential land use in Shandong Province in the past 10 years are significant. The five transition stages—from the primary stage, low stage, intermediate stage, advanced stage, to the stable stage—show obvious spatial agglomeration and spatial autocorrelation, which are mainly driven by the positive and negative interactions of economic development, the policy environment, natural conditions, and population. With the gradual upgrading of the land use scale in rural residential areas, the spatial pattern of rural residential areas has been continuously optimized, the land use structure has tended to be balanced and complicated, and the living-production-ecological function as a whole has been strengthened. The essence of this type of differentiation is the differential performance of rural residential areas adapting their own conditions to the external environment. The transition of the rural residential area from the macro to the micro scale is also the process of realizing rural reconstruction and rural revitalization. In the future, under the framework of the “element–structure–function” system of rural residential areas, the rural transition and development should be continuously promoted through the support, organization, guidance, and promotion mechanisms of internal and external factors.


Author(s):  
Qianshun Yuan ◽  
Sherehe Semba ◽  
Jing Zhang ◽  
Tongfeng Weng ◽  
Changgui Gu ◽  
...  

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 444
Author(s):  
Nicolae Dan Tesloianu ◽  
Lucian Dobreci ◽  
Vlad Ghizdovat ◽  
Andrei Zala ◽  
Adrian Valentin Cotirlet ◽  
...  

By assimilating biological systems, both structural and functional, into multifractal objects, their behavior can be described in the framework of the scale relativity theory, in any of its forms (standard form in Nottale’s sense and/or the form of the multifractal theory of motion). By operating in the context of the multifractal theory of motion, based on multifractalization through non-Markovian stochastic processes, the main results of Nottale’s theory can be generalized (specific momentum conservation laws, both at differentiable and non-differentiable resolution scales, specific momentum conservation law associated with the differentiable–non-differentiable scale transition, etc.). In such a context, all results are explicated through analyzing biological processes, such as acute arterial occlusions as scale transitions. Thus, we show through a biophysical multifractal model that the blocking of the lumen of a healthy artery can happen as a result of the “stopping effect” associated with the differentiable-non-differentiable scale transition. We consider that blood entities move on continuous but non-differentiable (multifractal) curves. We determine the biophysical parameters that characterize the blood flow as a Bingham-type rheological fluid through a normal arterial structure assimilated with a horizontal “pipe” with circular symmetry. Our model has been validated based on experimental clinical data.


2020 ◽  
Vol 29 (6) ◽  
pp. 133-142
Author(s):  
Seoung-Woong Park ◽  
Yong Jun Jo ◽  
Sukang Bae ◽  
Byung Hee Hong ◽  
Seoung-Ki Lee

2020 ◽  
Vol MA2020-02 (29) ◽  
pp. 1964-1964
Author(s):  
Hao Zhu ◽  
Hao Liu ◽  
Yang Wang ◽  
Zhenghao Gu ◽  
Kai Zhang ◽  
...  

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