The first types of transition metal complex cationic dye-sensitized 3D hybrid porous iodoplumbates exhibiting outstanding visible light-driven photoelectric properties.

POLAR, a joint European-Chinese experiment, is a novel compact space-borne Compton polarimeter conceived and optimized for detection of the prompt emission of Gamma-Ray Bursts (GRB) and precise measurements of polarization in the hard X-ray energy range 50-500 keV. The complete instrument consists of two parts: internal one, placed inside spacelab and the detector itself, placed outside spacelab, called respectively IBOX and OBOX. The OBOX constitutes of 25 frontend electronic modules (FEE), high voltage and low voltage power supplies and the Central Task Processing Unit. The main functions of Central Task Processing Unit system are defined as follows: communication and transfer of data to IBOX, communication with all frontends, analysis of trigger signals and generation of global trigger signals, data acquisition, synchronizing of all frontends and control of power supplies. The functional requirements are fulfilled by three individual FPGA chips named respectively to their functions: Concentrator, Trigger and CPU. This article presents description of the Central Task Processing Unit hardware design and brief introduction to main components of the firmware developed for this device. Ongoing integration activities of the device with the complete POLAR instrument proved that all basic functions are working correctly. The qualification model of the instrument has been constructed and currently undergoes verification and validation tests in view of planned flight onboard the Chinese spacelab TG-2 scheduled for 2015

Edited by Christian GriesingerKeywords: MPN domain JAMM motif COP9 signalosome CSN6 Crystal structure a b s t r a c tThe COP9 signalosome (CSN) is a multiprotein complex containing eight subunits and is highly conserved from fungi to human. CSN is proposed to widely participate in many physiological processes, including protein degradation, DNA damage response and signal transduction. Among those subunits, only CSN5 and CSN6 belong to JAMM family. CSN5 possesses isopeptidase activity, but CSN6 lacks this ability. Here we report the 2.5 Å crystal structure of MPN domain from Drosophila melanogaster CSN6. Structural comparison with other MPN domains, along with bioinformation analysis, suggests that MPN domain from CSN6 may serve as a scaffold instead of a metalloprotease. Structured summary of protein interactions:CSN6 and CSN6 bind by x-ray crystallography (View interaction) CSN6 and CSN6 bind by x ray scattering (View interaction)

Pixelated metasurfaces integrating both the functions of linear polarization and circular polarization filters on a single platform can achieve full-Stokes polarization detection. At present, the pixelated full-Stokes metasurfaces mainly face the following problems: low transmission, low circular dichroism (CD) of circular polarization filters, and high requirements in fabrication and integration. Herein, we propose high performance ultracompact all-dielectric pixelated full-Stokes metasurfaces in the near-infrared band based on silicon-on-insulator, which is compatible with the available semiconductor industry technologies. Circular polarization filters with high CD are achieved by using simple two-dimensional chiral structures, which can be easily integrated with the linear polarization filters on a single chip. In addition, the dielectric materials have higher transmission than metal materials with intrinsic absorption. We experimentally demonstrated the circular polarization filter with maximum CD up to 70% at a wavelength of 1.6 μm and average transmission efficiency above 80% from 1.48 μm to 1.6 μm. Therefore, our design is highly desirable for many applications, such as target detection, clinical diagnosis, and polarimetric imaging and sensing.

In recent years, although low-dimensional hybrid lead halides have received great attention due to the fascinating photoluminescent (PL) properties, the research is still on the early stage and only limited phases have been explored and characterized. Here, by introducing heterometals as mixed structural compositions and optical activity centers, we prepared a series of low-dimensional hybrid heterometallic halides, namely as, [(Me)-DABCO]2Cu2PbI6, [(Me)2-DABCO]2M5Pb2I13 (M = Cu and Ag) and [(Me)2-DABCO]­Ag2PbBr6 (Me = methyl group, DABCO = 1,4-diazabicyclo[2.2.2]­octane). These hybrid halides feature a low-dimensional 0D [Cu2PbI6]2– cluster, a 1D [M5Pb2I13]4– chain, and a 2D [Ag2PbBr6]2– layer, respectively, on the basis of corner-, edge- and face-sharing connecting of [MX4] tetrahedrons, [PbX5] quadrangular pyramids, and [PbX6] octahedrons. Under the photoexcitation, these hybrid heterometallic halides exhibit deep-red luminescent emissions from 711 to 801 nm with the largest Stocks shift of 395 nm. The temperature-dependent PL emissions, PL lifetime, and theoretical calculations are also investigated to probe into the intrinsic nature of photoluminescent emissions. This work affords new types of hybrid halides by introducing different metal centers to probe into the structural evolution and photoluminescent properties.

Advanced Driver Assistance Systems (ADAS) improve driving safety significantly. They alert drivers from unsafe traffic conditions when a dangerous maneuver appears. Traditional methods to predict driving maneuvers are mostly based on data-driven models alone. However, existing methods to understand the driver's intention remain an ongoing challenge due to a lack of intersection of human cognition and data analysis. To overcome this challenge, we propose a novel method that combines both the cognition-driven model and the data-driven model. We introduce a model named Cognitive Fusion-RNN (CF-RNN) which fuses the data inside the vehicle and the data outside the vehicle in a cognitive way. The CF-RNN model consists of two Long Short-Term Memory (LSTM) branches regulated by human reaction time. Experiments on the Brain4Cars benchmark dataset demonstrate that the proposed method outperforms previous methods and achieves state-of-the-art performance.

Every time after the taxi drivers drop off their previous passengers, they have to decide how to search for the next passengers. It may lead to poor performance if the taxi drivers cruise according to their own experience, especially for the freshmen. Therefore, it is valuable to recommend a profitable cruising route for the taxi drivers in order to increase their income and reduce waste in fuel. In this paper, we propose to use a system of linear equations to calculate the score of each road segment based on a large-scale real-world GPS data set. The score of each road segment consists of 1) the total income of the road segment and 2) the attractiveness of the drop-off location with respect to the next pick-up. Then, we get the profitable cruising route based on the score of each road segment using skyline computation. We build our system using historical data set generated by 12,000 taxis of Beijing in November 2012. Finally, we demonstrate that taxi driver who follows our recommendation can enhance their income compared to the ground truth.

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