A basic helix-loop-helix transcription factor, PhFBH4, regulates flower senescence by modulating ethylene biosynthesis pathway in petunia.

The basic helix-loop-helix (bHLH) transcription factors (TFs) play important roles in regulating multiple biological processes in plants. However, there are few reports about the function of bHLHs in flower senescence. In this study, a bHLH TF, PhFBH4, was found to be dramatically upregulated during flower senescence. Transcription of PhFBH4 is induced by plant hormones and abiotic stress treatments. Silencing of PhFBH4 using virus-induced gene silencing or an antisense approach extended flower longevity, while transgenic petunia flowers with an overexpression construct showed a reduction in flower lifespan. Abundance of transcripts of senescence-related genes (SAG12, SAG29) was significantly changed in petunia PhFBH4 transgenic flowers. Furthermore, silencing or overexpression of PhFBH4 reduced or increased, respectively, transcript abundances of important ethylene biosynthesis-related genes, ACS1 and ACO1, thereby influencing ethylene production. An electrophoretic mobility shift assay showed that the PhFBH4 protein physically interacted with the G-box cis-element in the promoter of ACS1, suggesting that ACS1 was a direct target of the PhFBH4 protein. In addition, ectopic expression of this gene altered plant development including plant height, internode length, and size of leaves and flowers, accompanied by alteration of transcript abundance of the gibberellin biosynthesis-related gene GA2OX3. Our results indicate that PhFBH4 plays an important role in regulating plant growth and development through modulating the ethylene biosynthesis pathway

Convolutional Neural Networks combined with Runge-Kutta Methods

A convolutional neural network for image classification can be constructed mathematically since it can be regarded as a multi-period dynamical system. In this paper, a novel approach is proposed to construct network models from the dynamical systems view. Since a pre-activation residual network can be deemed an approximation of a time-dependent dynamical system using the forward Euler method, higher order Runge-Kutta methods (RK methods) can be utilized to build network models in order to achieve higher accuracy. The model constructed in such a way is referred to as the Runge-Kutta Convolutional Neural Network (RKNet). RK methods also provide an interpretation of Dense Convolutional Networks (DenseNets) and Convolutional Neural Networks with Alternately Updated Clique (CliqueNets) from the dynamical systems view. The proposed methods are evaluated on benchmark datasets: CIFAR-10/100, SVHN and ImageNet. The experimental results are consistent with the theoretical properties of RK methods and support the dynamical systems interpretation. Moreover, the experimental results show that the RKNets are superior to the state-of-the-art network models on CIFAR-10 and on par on CIFAR-100, SVHN and ImageNet

Tight and attainable quantum speed limit for open systems

We develop an intuitive geometric picture of quantum states, define a particular state distance, and derive a quantum speed limit (QSL) for open systems. Our QSL is attainable because any initial state can be driven to a final state by the particular dynamics along the geodesic. We present the general condition for dynamics along the geodesic for our QSL. As evidence, we consider the generalized amplitude damping dynamics and the dephasing dynamics to demonstrate the attainability. In addition, we also compare our QSL with others by strict analytic processes as well as numerical illustrations, and show our QSL is tight in many cases. It indicates that our work is significant in tightening the bound of evolution time

Establishing National Carbon Emission Prices for China

The purpose of the paper is to establish national carbon emissions prices for the People’s Republic of China, which is one of the world’s largest producers of carbon emissions. Several measures have been undertaken to address climate change in China, including the establishment of a carbon trading system. Since 2013, eight regional carbon emissions markets have been established, namely Beijing, Shanghai, Guangdong, Shenzhen, Tianjin, Chongqing, Hubei and Fujian. The Central Government announced a national carbon emissions market, with power generation as the first industry to be considered. However, as carbon emissions prices in the eight regional markets are very different, for a variety of administrative reasons, it is essential to create a procedure for establishing a national carbon emissions price. The regional markets are pioneers, and their experience will play important roles in establishing a national carbon emissions market, with national prices based on regional prices, turnovers and volumes. The paper considers two sources of regional data for China’s carbon allowances, which are based on primary and secondary data sources, and compares their relative strengths and weaknesses. The paper establishes national carbon emissions prices based on the primary and secondary regional prices, for the first time, and compares both national prices and regional prices against each other. The carbon emission prices in Hubei, Guangdong, Shenzhen and Tianjin are highly correlated with the national prices based on the primary and secondary sources. Establishing national carbon emissions prices should be very helpful for the national carbon emissions market that is under construction in China, as well as for other regions and countries worldwide

Human-Automation Allocations for Current Robotic Space Operations: Space Station Remote Manipulator System

NASAs Human Research Programs Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) delineates the uncertainty surrounding crew work with automation and robotics in spaceflight. HARI is concerned with detrimental effects of ineffective user interfaces, system designs and/or functional task allocation on crew performance, potentially compromising mission success and safety. This risk arises because of limited experience with complex automation and robotics in spaceflight. One key knowledge gap within the HARI risk is related to function allocation

Ethical Practices in Facilitating Learning and Improving Educational Technology and Alternative Education by Using Google Classroom

The globalization period has ushered in a race among nations to develop, adopt, and master new technology. Using technology in education is one of the most effective methods to do this. Utilizing education-based technologies, such as Google Classroom, can help Philippines Woman University (PWU) overcome the barriers to the adoption of online learning. Google Classroom has a distinct look and feel, like many new programs that emerge. Google Classroom is a component of the Google Apps for Education (GAFE) online suite of productivity tools for instructors and learners using the internet. This program offers a centralized location for interacting with students, offering feedback, and assigning assignments. Google Classroom has implications for how education is implemented in Philippines Woman University (PWU), including how teachers are evaluated, how students use technology, and more