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Understanding how the brain captures transient experience and converts it into long lasting changes in neural circuits requires the identification and investigation of the specific ensembles of neurons that are responsible for the encoding of each experience. We have developed a Robust Activity Marking (RAM) system that allows for the identification and interrogation of ensembles of neurons. The RAM system provides unprecedented high sensitivity and selectivity through the use of an optimized synthetic activity-regulated promoter that is strongly induced by neuronal activity and a modified Tet-Off system that achieves improved temporal control. Due to its compact design, RAM can be packaged into a single adeno-associated virus (AAV), providing great versatility and ease of use, including application to mice, rats, flies, and potentially many other species. Cre-dependent RAM, CRAM, allows for the study of active ensembles of a specific cell type and anatomical connectivity, further expanding the RAM system’s versatility.DOI: http://dx.doi.org/10.7554/eLife.13918.001

Emotion analysis of on-line user generated textual content is important for natural language processing and social media analytics tasks. Most of previous emotion analysis approaches focus on identifying users’ emotional states from text by classifying emotions into one of the finite categories, e.g., joy, surprise, anger and fear. However, there exists ambiguity characteristic for the emotion analysis, since a single sentence can evoke multiple emotions with different intensities. To address this problem, we introduce emotion distribution learning and propose a multi-task convolutional neural network for text emotion analysis. The end-to-end framework optimizes the distribution prediction and classification tasks simultaneously, which is able to learn robust representations for the distribution dataset with annotations of different voters. While most work adopt the majority voting scheme for the ground truth labeling, we also propose a lexiconbased strategy to generate distributions from a single label, which provides prior information for the emotion classification. Experiments conducted on five public text datasets (i.e., SemEval, Fairy Tales, ISEAR, TEC, CBET) demonstrate that our proposed method performs favorably against the state-of-the-art approaches.

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As a typical kinds of toxic gases, CO plays an important role in environmental monitoring, control of chemical processes, space missions, agricultural and medical applications. Graphene is considered a potential candidate of gases sensor, so the adsorption of CO molecules on various graphene, including pristine graphene, Nitrogen-doped graphene (N-doped graphene) and Aluminum-doped graphene (Al-doped graphene), are studied by using first-principles calculations. The optimal configurations, adsorption energies, charge transfer, and electronic properties including band structures, density of states and differential charge density are obtained. The adsorption energies of CO molecules on pristine graphene and N-doped graphene are −0.01 eV, and −0.03 eV, respectively. In comparison, the adsorption energy of CO on Al-doped graphene is much larger, −2.69 eV. Our results also show that there occurs a large amount of charge transfer between CO molecules and graphene sheet after the adsorption, which suggests Al-doped graphene is more sensitive to the adsorption of CO than pristine graphene and N-doped graphene. Therefore, the sensitivity of gases on graphene can be drastically improved by introducing the suitable dopants.

and fair theoretical specifi c capacity (197 mAh g −1 for complete extraction of three lithium ions when charged to 4.8 V, 133 mAh g −1 when cycled between the potential window of 3.0-4.3 V). [12][13][14] In particular, because of its sodium super ionic conductor (NASICON) structure, monoclinic Li 3 V 2 (PO 4 ) 3 provides a 3D pathway for Li + insertion/ extraction, which results in a very high ion diffusion coeffi cient (from 10 −9 to 10 −10 cm 2 s −1 ). [15][16][17][18][19] However, Li 3 V 2 (PO 4 ) 3 suffers a poor electronic conductivity (2.4 × 10 −7 S cm −1 at room temperature) due to the nature of its separated VO 6 octahedral arrangement, which significantly limits its rate performance and the further commercialization. [20][21][22][23][24] Carbon coating is an economic and feasible technique that is widely used to improve the electronic conductivity. [ 14,17,[25][26][27][28] However, the common carbon coating could only provide an electron pathway on the nanoscale for individual particles. In comparison, the architecture combining the nanoscale carbon coating and the microscale carbon network could provide hierarchical pores for the electrolyte to pass through, which may supply a highly conductive network for both electrons and lithium ions, promoting the fast charge/discharge processes. [ 6,[29][30][31][32] In addition, the fast kinetics enabled by this architecture would be benefi cial for the battery performance at low temperature, which is a key issue in the application.Here, we propose a feasible and environmentally friendly one-pot method utilizing glucose as both the carbon source and the reducing agent (functioned by the aldehyde group). Via the optimization of the interface reaction, hierarchical carbon (nanoscale amorphous carbon coating and microscale carbon network) decorated Li 3 V 2 (PO 4 ) 3 is obtained (Schematic, Figure 1 ). This unique architecture can provide the following three important features simultaneously: 1) continuous electron conduction enabled by hierarchical carbon, 2) rapid ion transport enabled by electrolyte-fi lled macro/ mesopore network, and 3) a buffered protective carbon shell. The obtained cathode material achieved an enhanced rate capability (121 mAh g −1 at rate up to 30 C), superior cycling stability Developing rechargeable lithium ion batteries with fast charge/discharge rate, high capacity and power, long lifespan, and broad temperature adaptability is still a signifi cant challenge. In order to realize the fast and effi cient transport of ions and electrons during the charging/discharging process, a 3D hierarchical carbon-decorated Li 3 V 2 (PO 4 ) 3 is designed and synthesized with a nanoscale amorphous carbon coating and a microscale carbon network. The Brunauer-Emmett-Teller (BET) surface area is 65.4 m 2 g −1 and the porosity allows for easy access of the electrolyte to the active material. A specifi c capacity of 121 mAh g −1 (91% of the theoretical capacity) can be obtained at a rate up to 30 C. When cycled at a rate of 20 C, the capacity retention is 77...

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