The role of connectivity in significant bandgap narrowing for fused-pyrene based non-fullerene acceptors toward high-efficiency organic solar cells

Great attention has been paid to developing low bandgap non-fullerene acceptors (NFAs) for matching wide bandgap donor polymers to increase the photocurrent and therefore the power conversion efficiencies (PCEs) of NFA organic solar cells, while pyrene-core based acceptor-donor-acceptor (A-D-A) NFAs have been mainly reported via the 2,9-position connection due to their bisthieno[3′,2′-b']thienyl[a,h]pyrene fused via a five-membered ring bridge at the ortho-position of pyrene as the representative one named FPIC5, which has prohibited further narrowing their energy gap. Herein, an acceptor FPIC6 was exploited by creating the 1,8-position connection through fusing as bisthieno[3′,2′-b′]thienyl[f-g,m-n]pyrene linked at the bay-position via a six-membered bridge, with enhanced push-pull characteristics within such A-D-A structure. As a structural isomer of FPIC5, FPIC6 exhibited a much lower bandgap of 1.42 eV (1.63 eV for FPIC5). Therefore, the photocurrent and PCE of PTB7-Th:FPIC6 cells were improved to 21.50 mA cm-2 and 11.55%, respectively, due to the balanced mobilities, better photoluminescence quenching efficiency and optimized morphology, which are both ∼40% better than those of PTB7-Th:FPIC5 cells. Our results clearly proved that a pyrene fused core with 1,8-position connection with electron-withdrawing end groups instead of 2,9-position connection is an efficient molecular design strategy to narrow the optical bandgap and improve the photovoltaic performance of NFA based OSCs

Neonatal rhesus monkey is a potential animal model for studying pathogenesis of EV71 infection

AbstractData from limited autopsies of human patients demonstrate that pathological changes in EV71-infected fatal cases are principally characterized by clear inflammatory lesions in different parts of the CNS; nearly identical changes were found in murine, cynomolgus and rhesus monkey studies which provide evidence of using animal models to investigate the mechanisms of EV71 pathogenesis. Our work uses neonatal rhesus monkeys to investigate a possible model of EV71 pathogenesis and concludes that this model could be applied to provide objective indicators which include clinical manifestations, virus dynamic distribution and pathological changes for observation and evaluation in interpreting the complete process of EV71 infection. This induced systemic infection and other collected indicators in neonatal monkeys could be repeated; the transmission appears to involve infecting new monkeys by contact with feces of infected animals. All data presented suggest that the neonatal rhesus monkey model could shed light on EV71 infection process and pathogenesis

IL-17A Synergizes with IFN-γ to Upregulate iNOS and NO Production and Inhibit Chlamydial Growth

IFN-γ-mediated inducible nitric oxide synthase (iNOS) expression is critical for controlling chlamydial infection through microbicidal nitric oxide (NO) production. Interleukin-17A (IL-17A), as a new proinflammatory cytokine, has been shown to play a protective role in host defense against Chlamydia muridarum (Cm) infection. To define the related mechanism, we investigated, in the present study, the effect of IL-17A on IFN-γ induced iNOS expression and NO production during Cm infection in vitro and in vivo. Our data showed that IL-17A significantly enhanced IFN-γ-induced iNOS expression and NO production and inhibited Cm growth in Cm-infected murine lung epithelial (TC-1) cells. The synergistic effect of IL-17A and IFN-γ on Chlamydia clearance from TC-1 cells correlated with iNOS induction. Since one of the main antimicrobial mechanisms of activated macrophages is the release of NO, we also examined the inhibitory effect of IL-17A and IFN-γ on Cm growth in peritoneal macrophages. IL-17A (10 ng/ml) synergizes with IFN-γ (200 U/ml) in macrophages to inhibit Cm growth. This effect was largely reversed by aminoguanidine (AG), an iNOS inhibitor. Finally, neutralization of IL-17A in Cm infected mice resulted in reduced iNOS expression in the lung and higher Cm growth. Taken together, the results indicate that IL-17A and IFN-γ play a synergistic role in inhibiting chlamydial lung infection, at least partially through enhancing iNOS expression and NO production in epithelial cells and macrophages

The CHEMDNER corpus of chemicals and drugs and its annotation principles

The automatic extraction of chemical information from text requires the recognition of chemical entity mentions as one of its key steps. When developing supervised named entity recognition (NER) systems, the availability of a large, manually annotated text corpus is desirable. Furthermore, large corpora permit the robust evaluation and comparison of different approaches that detect chemicals in documents. We present the CHEMDNER corpus, a collection of 10,000 PubMed abstracts that contain a total of 84,355 chemical entity mentions labeled manually by expert chemistry literature curators, following annotation guidelines specifically defined for this task. The abstracts of the CHEMDNER corpus were selected to be representative for all major chemical disciplines. Each of the chemical entity mentions was manually labeled according to its structure-associated chemical entity mention (SACEM) class: abbreviation, family, formula, identifier, multiple, systematic and trivial. The difficulty and consistency of tagging chemicals in text was measured using an agreement study between annotators, obtaining a percentage agreement of 91. For a subset of the CHEMDNER corpus (the test set of 3,000 abstracts) we provide not only the Gold Standard manual annotations, but also mentions automatically detected by the 26 teams that participated in the BioCreative IV CHEMDNER chemical mention recognition task. In addition, we release the CHEMDNER silver standard corpus of automatically extracted mentions from 17,000 randomly selected PubMed abstracts. A version of the CHEMDNER corpus in the BioC format has been generated as well. We propose a standard for required minimum information about entity annotations for the construction of domain specific corpora on chemical and drug entities. The CHEMDNER corpus and annotation guidelines are available at: http://www.biocreative.org/resources/biocreative-iv/chemdner-corpus

Takagi-Sugeno Fuzzy Model-Based Semi-Active Control for the Seat Suspension with an Electrorheological Damper

Numerous research studies have been performed to help develop advanced control algorithms for semi-active seat suspension. This paper experimentally investigates a state observer-based Takagi-Sugeno (T-S) fuzzy controller for a semi-active seat suspension by equipping an electrorheological (ER) damper. A new ER damper prototype is designed, assembled, and tested. Then, a T-S fuzzy model is established to describe the ER seat suspension, which can facilitate the $\text{H}\infty$ controller design considering the multi-objective optimization. A state observer is established and integrated into the controller to estimate the state information for the T-S fuzzy model in real-time. Additionally, the experimental validation of the control algorithm is critical in the practical application. A seat suspension test rig is built to validate the effectiveness of the proposed controller. The presented control algorithm is evaluated by comparing the corresponding test results to those with a skyhook controller. The experimental results demonstrate that the proposed T-S fuzzy control method, compared to the traditional control method, can further improve the performance of an ER seat suspension system

A takagi-sugeno fuzzy model-based control strategy for variable stiffness and variable damping suspension

© 2013 IEEE. As the concept of variable stiffness and variable damping (VSVD) has increasingly drawn attention, suspensions applied with magnetorheological (MR) dampers to achieve varying stiffness and damping have been an attractive method to improve vehicle performance and driver comfort further. As highly nonlinearity of MR damper dynamics and coupled interconnections in the case of multi-output control, to build a direct control system for VSVD suspension based on multiple MR dampers is difficult. Applying Takagi-Sugeno (T-S) fuzzy model on the VSVD system enables the linear control theory to be directly utilized to build the multi-output controller for multi-MR dampers. In this paper, a T-S fuzzy model is established to describe an MR VSVD suspension model, and then an H∞ controller that considers the multi-input/multi-output (MIMO) coupled interconnections characteristic and multi-object optimization is designed. To estimate state information for the T-S fuzzy model in real-time, a state observer is designed and integrated in the controller. Then, the performance of the VSVD control algorithm was evaluated by numerical simulation. The results demonstrate that the T-S fuzzy model-based H&infty; controller outperforms the independent control method for a VSVD suspension system with multi-MR dampers

A New Generation of Magnetorheological Vehicle Suspension System With Tunable Stiffness and Damping Characteristics

As the concept of variable stiffness (VS) and variable damping (VD) has increasingly drawn attention because of its superiority on reducing unwanted vibrations, dampers with property of varying stiffness and damping have been an attractive method to further improve vehicle performance and driver comfort. This paper presents the design, prototyping, modeling, and experimental evaluation of a VS and VD magnetorheological (MR) vehicle suspension system. It was first characterized by an INSTRON machine. Then, a phenomenological model was proposed to capture the characteristics of the damper and TS fuzzy approach was used to model the quarter car system where the proposed damper was installed. Different controllers, including skyhook, short-time Fourier transform and state observer based controller were designed to control the damper. Experimental results demonstrate that the quarter car system with the VS and VD suspension performs best in terms of reducing the sprung mass accelerations comparing with other suspensions

RAMZzz : rank-aware DRAM power management with dynamic migrations and demotions

Main memory is a significant energy consumer which may contribute to over 40% of the total system power, and will become more significant for server machines with more main memory. In this paper, we propose a novel memory system design named RAMZzz with rank-aware energy saving optimizations. Specifically, we rely on a memory controller to monitor the memory access locality, and group the pages with similar access locality into the same rank. We further develop dynamic page migrations to adapt to data access patterns, and a prediction model to estimate the demotion time for accurate control on power state transitions. We experimentally compare our algorithm with other energy saving policies with cycle-accurate simulation. Experiments with benchmark workloads show that RAMZzz achieves significant improvement on energy-delay2 and energy consumption over other power saving techniques