Selective Adsorption of Dyes and Fe Sensing via Tb Incorporation in an Anionic Cadmium-Organic Framework.

A three-dimensional (3D) anionic cadmium-organic framework, namely [(CH)NH][Cd(DMTDC)] ⋅ 2DMA ⋅ 0.5HO (Cd-MOF; DMA=N,N-dimethylacetamide), was successfully synthesized under solvothermal conditions by using a linear thienothiophene-containing dicarboxylate ligand, 3,4-dimethylthieno [2,3-b]-thiophene-2,5-dicar-boxylic acid (HDMTDC). Single-crystal X-ray diffraction analysis reveals that Cd-MOF exhibits a 3D anionic framework with pcu α-Po topology, featuring rectangle and rhombus-shaped channels along b- and c- axis direction.

Changing visions in ESP development and teaching: Past, present, and future vistas.

Globalization and international development in language education have inspired a shift from the learning of traditional College English to English for Specific Purposes (ESP). This article begins with a section on the methodology used to develop the literature review. From various literatures, a historical perspective was first presented for the period, 1962 to the present day, and accompanied by a review on the teaching approaches.

A leader-following paradigm based deep reinforcement learning method for multi-agent cooperation games.

Multi-agent deep reinforcement learning algorithms with centralized training with decentralized execution (CTDE) paradigm has attracted growing attention in both industry and research community. However, the existing CTDE methods follow the action selection paradigm that all agents choose actions at the same time, which ignores the heterogeneous roles of different agents. Motivated by the human wisdom in cooperative behaviors, we present a novel leader-following paradigm based deep multi-agent cooperation method (LFMCO) for multi-agent cooperative games.

Multistep Multiagent Reinforcement Learning for Optimal Energy Schedule Strategy of Charging Stations in Smart Grid.

An efficient energy scheduling strategy of a charging station is crucial for stabilizing the electricity market and accommodating the charging demand of electric vehicles (EVs). Most of the existing studies on energy scheduling strategies fail to coordinate the process of energy purchasing and distribution and, thus, cannot balance the energy supply and demand. Besides, the existence of multiple charging stations in a complex scenario makes it difficult to develop a unified schedule strategy for different charging stations.

Towards Stochastic Optimization-Based Electric Vehicle Penetration in a Novel Archipelago Microgrid.

Due to the advantage of avoiding upstream disturbance and voltage fluctuation from a power transmission system, Islanded Micro-Grids (IMG) have attracted much attention. In this paper, we first propose a novel self-sufficient Cyber-Physical System (CPS) supported by Internet of Things (IoT) techniques, namely "archipelago micro-grid (MG)", which integrates the power grid and sensor networks to make the grid operation effective and is comprised of multiple MGs while disconnected with the utility grid. The Electric Vehicles (EVs) are used to replace a portion of Conventional Vehicles (CVs) to reduce CO 2 emission and operation cost.

Highly selective luminescence sensing for Cu2+ ions and selective CO2 capture in a doubly interpenetrated MOF with Lewis basic pyridyl sites.

A doubly interpenetrated MOF was constructed using a new pyridyl carboxylate ligand with active pyridyl sites, which exhibits highly efficient luminescence sensing for Cu(2+) ions and sorption selectivities of CO2 over CH4 and N2.