Myopic Versus Farsighted Behaviors in a Low-Carbon Supply Chain with Reference Emission Effects

The increased carbon emissions cause relatively climate deterioration and attract more attention of governments, consumers, and enterprises to the low-carbon manufacturing. This paper considers a dynamic supply chain, which is composed of a manufacturer and a retailer, in the presence of the cap-and-trade regulation and the consumers’ reference emission effects. To investigate the manufacturer’s behavior choice and its impacts on the emission reduction and pricing strategies together with the profits of both the channel members, we develop a Stackelberg differential game model in which the manufacturer acts in both myopic and farsighted manners. By comparing the equilibrium strategies, it can be found that the farsighted manufacturer always prefers to keep a lower level of emission reduction. When the emission permit price is relatively high, the wholesale/retail price is lower if the manufacturer is myopic and hence benefits consumers. In addition, there exists a dilemma that the manufacturer is willing to act in a farsighted manner but the retailer looks forward to a partnership with the myopic manufacturer. For a relatively high price of emission permit, adopting myopic strategies results in a better performance of the whole supply chain

Local vibration characteristics of rotating blades induced by moving rub-impact loads

Considering spin softening and centrifugal stiffening effect of blades, the parameterized finite element model of rotating blades with moving rub-impact loads is established. Time domain response and frequency domain response are analyzed along with the change of speed and local vibration characteristic of the blade is studied under the different harmonic components. With investigation of the rotating blades, some conclusions have been found: The displacement caused by centrifugal effect has a maximum amplitude at blade tip and appears a smaller amplitude at blade root. And the stress change is just the opposite, which is basically a linear relation with location, and stress value caused by the centrifugal effect is basically in direct proportion to square of rotation speed within a certain range. Rub-impact can induced a variety of frequency multiplication components of the rotating blades, which cause different levels vibration response of the blade. The corresponding high-frequency components of the local stress mostly appear at angular position and root position of blade, which is easy to cause local fatigue damage of blade. Therefore, it need pay more attention to avoid frequency multiplication omponents caused by rub-impact approaching the natural frequency of the blade in order to prevent from local vibration. The results of the study in this paper will provide theoretical reference for the characteristic analysis and fault diagnosis of similar rotating blades

The arabidopsis RCC1 family protein TCF1 regulates freezing tolerance and cold acclimation through modulating lignin biosynthesis

Cell water permeability and cell wall properties are critical to survival of plant cells during freezing, however the underlying molecular mechanisms remain elusive. Here, we report that a specifically cold-induced nuclear protein, Tolerant to Chilling and Freezing 1 (TCF1), interacts with histones H3 and H4 and associates with chromatin containing a target gene, BLUE-COPPER-BINDING PROTEIN (BCB), encoding a glycosylphosphatidylinositol-anchored protein that regulates lignin biosynthesis. Loss of TCF1 function leads to reduced BCB transcription through affecting H3K4me2 and H3K27me3 levels within the BCB gene, resulting in reduced lignin content and enhanced freezing tolerance. Furthermore, plants with knocked-down BCB expression (amiRNA-BCB) under cold acclimation had reduced lignin accumulation and increased freezing tolerance. The pal1pal2 double mutant (lignin content reduced by 30% compared with WT) also showed the freezing tolerant phenotype, and TCF1 and BCB act upstream of PALs to regulate lignin content. In addition, TCF1 acts independently of the CBF (C-repeat binding factor) pathway. Our findings delineate a novel molecular pathway linking the TCF1-mediated cold-specific transcriptional program to lignin biosynthesis, thus achieving cell wall remodeling with increased freezing tolerance

Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems

The demand of probabilistic time series forecasting has been recently raised in various dynamic system scenarios, for example, system identification and prognostic and health management of machines. To this end, we combine the advances in both deep generative models and state space model (SSM) to come up with a novel, data-driven deep probabilistic sequence model. Specially, we follow the popular encoder-decoder generative structure to build the recurrent neural networks (RNN) assisted variational sequence model on an augmented recurrent input space, which could induce rich stochastic sequence dependency. Besides, in order to alleviate the issue of inconsistency between training and predicting as well as improving the mining of dynamic patterns, we (i) propose using a hybrid output as input at next time step, which brings training and predicting into alignment; and (ii) further devise a generalized auto-regressive strategy that encodes all the historical dependencies at current time step. Thereafter, we first investigate the methodological characteristics of the proposed deep probabilistic sequence model on toy cases, and then comprehensively demonstrate the superiority of our model against existing deep probabilistic SSM models through extensive numerical experiments on eight system identification benchmarks from various dynamic systems. Finally, we apply our sequence model to a real-world centrifugal compressor sensor data forecasting problem, and again verify its outstanding performance by quantifying the time series predictive distribution.Comment: 25 pages, 7 figures, 4 tables, preprint under revie