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Springer即将截止的特刊征稿二月辑|寻找更匹配您的投稿方向

已有 1764 次阅读 2023-2-16 11:04 |个人分类:期刊精选|系统分类:博客资讯

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特刊:Special Issue on "Complex Ginzburg-Landau Equation"

期刊:Journal of Nonlinear Mathematical Physics

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客座编辑:Mário Ferreira & Boris Malomed

This Special Issue aims to collect a set of high-quality works reporting recent achievements and future challenges produced by the ongoing work on CGL equations and their applications. We sincerely invite submission of new theoretical and experimental results dealing with but not limited to the following topics:

  • Dissipative solitons, vortices, and other localized and delocalized regular states generated by one-, two-, and three-dimensional NLS equations and systems of such coupled equations

  • Chaotic dynamics and turbulence modeled by CGL equations

  • Relations of CGL equations to parity-time symmetric systems

  • Physical realizations of CGL equations

  • Traditional applications of CGL equations to superconductivity (this is the area in which the Ginzburg-Landau equations had appeared 70 years ago)

  • Numerical and analytical methods developed for the work with CGL equations

  • Review articles on these and related topics

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特刊:Database and Artificial Intelligence

期刊:Data Science and Engineering

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客座编辑:Guoliang Li, Zhifeng Bao, Dong Deng & Ce Zhang

Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can make database more intelligent (AI4DB). For example, traditional empirical database optimization techniques (e.g., cost estimation, join order selection, knob tuning, index and view advisor) cannot meet the high-performance requirement for large-scale database instances, various applications and diversified users, especially on the cloud. Fortunately, learning-based techniques can alleviate this problem. On the other hand, database techniques can optimize AI models (DB4AI). For example, AI is hard to deploy, because it requires developers to write complex codes and train complicated models. Database techniques can be used to reduce the complexity of using AI models, accelerate AI algorithms and provide AI capability inside databases. DB4AI and AI4DB have been extensively studied recently. In this special issue, we invite high-quality submissions for database for AI and AI for database.

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特刊:Energy Sustainability, Vulnerability and Resilience

期刊:Discover Sustainability

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客座编辑:Andrea Gatto, Luigi ALDIERI, Demetrio Panarello & Elkhan Richard Sadik-Zada

Our society is demanded to deal with increasing ecological, inequality, political and economic concerns. Energy is a key aspect to be addressed when facing sustainability challenges. Undertaking sustainable energy pathways implies considering a number of intertwined problematics, including energy vulnerability and energy resilience. Energy sustainability is also a priority in the current development agenda and countries are required to foster action plans oriented towards cleaner, more sustainable and renewable energy. Households and individuals are also asked to follow energy adaptation and mitigation strategies. Virtuous energy policies will facilitate energy resilience targets, suggesting protection patterns for the most vulnerable socioeconomic groups.

The Topical Collection aims to receive contributions tackling energy sustainability, energy vulnerability and energy resilience aspects, as well as papers related to these subjects. Any of these three topics may be approached. These include:

  • Energy sustainability;

  • Energy vulnerability;

  • Energy resilience;

  • Climate change mitigation and adaptation;

  • Energy and ecological transition;

  • Energy metrics;

  • Energy prices analysis;

  • Energy policy and regulation.

  • Further energy sustainability topics (energy justice, security, poverty, emergy, etc.).

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特刊:Artificial intelligence in Energy Management

期刊:Discover Artificial Intelligence

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客座编辑:Behnam Mohammadi-Ivatloo, Hossein Yousefi & Ghazaleh Amini

This collection focuses on the role of Artificial Intelligence in energy management.

The application of Artificial Intelligence in energy management and furthere increase in penetration of renewable energy sources is undeniable due to high complexity associated with integrated energy systems and need to real-time prediction to manage its resources efficiently with reasonable computation burden (as low as possible) and satisfy the demand. To move toward energy and environment sustainability and mitigating the environment-friendly technologies, are role of Artificial Intelligence in critical. Artificial Intelligence techniques improve the operation and productivity of the power system by controlling voltage, load frequency, stability, power flow, and also mitigating probabilistic conditions in such systems. Such techniques can identify the fault type and related location in energy transmission systems based on the value of line parameters. It is necessary to identify the suitable Artificial intelligence technique for every problem in energy systems. The performance of Artificial Intelligence-based forecasting methods are evaluated from five aspects, i.e., the type of studied energy system (like building and microgrid), the methods used for prediction, the type of predicted energies (like electricity, thermal, and cooling), the time scale of the prediction (like daily prediction), and the type of input data used for prediction.

Artificial Intelligence has several advantages compared to other methods. It needs less detailed physical information of energy systems. This saves both time and cost of the prediction. Promising forecasting accuracy can be achieved by Artificial Intelligence once the model is well trained. However, Artificial Intelligence have some drawbacks including unexplicit relation between the physical system parameters and model inputs, need to historical energy system data, need to extensive training data for model creation and retaining forecasting quality, and need to re-training once changes are made to physical and operation characteristics of energy system.

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特刊:BRICS Carbon

期刊:Carbon Research

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客座编辑:Yilai Lou, Sartaj Ahmad Bhat, Liangshan Feng, Risely Ferraz-Almeida,  Olga Nesterva, Rishikesh Singh  & Antoninova Natalya Yurievna

During the 2022 BRICS conference, the five BRICS countries of Brazil, Russia, India, China and South Africa have greatly focused on sustainable development. The environment pollution and climate change present a huge threat to the human-being of our time. Better understanding ecosystem carbon and nitrogen cycling processes and developing more effective strategies in sequestering carbon and alleviating greenhouse gas emissions are urgent needs to optimize ecosystem services. Additionally, engineered carbonaceous materials such as biochar and bioplastics have been increasingly developed and applied to remedy environmental contamination, to restore degraded ecosystems and to mitigate climate change. This special issue specially focusing on the latest advances in carbon-nitrogen cycling and management of ecosystems and engineered carbonaceous materials in BRICS countries aims to promote scholarly communications among the BRICS countries and to share the relevant research achievements to the world. This will be significant for advancing the relevant scientific field and for informing carbon management and carbonaceous material application for a sustainable world.

Possible Topics:

• Engineered carbonaceous materials (e.g., biochar, bioplastics, nanomaterials, catalysts etc.) and their applications to environmental remediation and restoration;

• Natural carbonaceous materials (e.g., humic substances, natural organic matter, cellulose, black carbon, etc.) and their biogeochemical cycling and ecological functions; Carbon and renewable energy generation;

• Carbon cycle, non-CO2 greenhouse gases and global change;

• Carbon neutrality and carbon-negative technologies;

• Other related novel sciences and technologies with global perspectives.

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特刊:CO2 Reduction: The Quest for Electrocatalytic Materials

期刊:SN Applied Sciences

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客座编辑:David Wakerley

Rising levels of carbon dioxide (CO2) are of significant concern in modern society, as they lead to global warming and consequential environmental and societal changes. It is of importance to develop industries with a zero or negative CO2 footprint. Electrochemistry, where one of the reagents is electrons, is an environmentally clean technology that is capable of addressing the conversion of CO2 to value-added products. The key factor in the process is the use of catalytic electrode materials that lead to the desired reaction and product. Significant progress in this field has been achieved in the past two years. This topical collection is interested in progress in the development of electrocatalysts for CO2 reduction achieved during this time period.

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特刊:Organic light emitting diodes

期刊:Scientific Reports

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客座编辑:Annalisa Bruno, Andrew Grimsdale & Yuh-Renn Wu

Organic light emitting diodes (OLEDs) are emitting diodes where the emission layer is an organic compound such as molecules or polymers. OLEDs build on an essential property of organic materials: high efficient luminescence. They are largely used in our daily life for indoor lighting and also in various display devices such as TV screens, computer monitors, and transparent displays in mobile phones. OLEDs have also shown potential for future ultra-thin and flexible technologies. For all of these reasons, and also for their cost advantages, academic and industry researchers have made a great effort in pushing further OLED technologies in recent years.

This Collection showcases original research in organic light emitting diodes, covering the latest advances in luminescent materials for OLEDs as well as research on the fabrication and characterisation of OLEDs for the next generation of displays and solid-state lighting applications.

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特刊:Conservation ecology in agricultural systems

期刊:Scientific Reports

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客座编辑:Ngonidzashe Chirinda, Eve Veromann & Johann G. Zaller

A large part of the world’s terrestrial surface has been transformed by agriculture, reshaping the natural environment. Many species have been lost or are endangered due to mismanaged agricultural practices, be it habitat destruction, over-exploitation of resources, use of pesticides, and many other factors. However, recent decades have seen more environmentally sustainable approaches implemented, including strategies to preserve and even enhance biodiversity.

This Collection offers a platform for the latest research on conservation ecology and biodiversity preservation in agricultural systems including, but not limited to, multidisciplinary studies in the fields of agroecology, agroforestry, landscape ecology, and sustainable development.

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