Enhancing the Efficiency of Organic Photovoltaics by a Photoactive Molecular Mediator

High boiling-point solvent additives, such as 1,8-diiodooctane, have been widely used to tune nanoscale phase morphology for increased efficiency in bulk heterojunction organic solar cells. However, liquid-state solvent additives remain in the active films for extended times and later migrate or evaporate from the films, leading to unstable device performance. Here, a solid-state photoactive molecular mediator, namely N(BAI)3, is reported that could be employed to replace the commonly used solvent additives to tune the morphology of bulk heterojunction films for improved device performance. The N(BAI)3 mediator not only resides in the active films locally to fine tune the phase morphology, but also contributes to the additional absorption of the active films, leading to ∼11% enhancement of power conversion efficiency of P3HT:PC60BM devices. Comparative studies are carried out to probe the nanoscale morphologies using grazing incidence wide-angle X-ray scattering and complementary neutron reflectometry. The use of 1 wt% N(BAI)3 is found to effectively tune the packing of P3HT, presumably through balanced π-interactions endowed by its large conjugated π surface, and to promote the formation of a PC60BM-rich top interfacial layer. These findings open up a new way to effectively tailor the phase morphology by photoactive molecular mediators in organic photovoltaics

Rectifying Unfairness in Recommendation Feedback Loop

The issue of fairness in recommendation systems has recently become a matter of growing concern for both the academic and industrial sectors due to the potential for bias in machine learning models. One such bias is that of feedback loops, where the collection of data from an unfair online system hinders the accurate evaluation of the relevance scores between users and items. Given that recommendation systems often recommend popular content and vendors, the underlying relevance scores between users and items may not be accurately represented in the training data. Hence, this creates a feedback loop in which the user is not longer recommended based on their true relevance score but instead based on biased training data. To address this problem of feedback loops, we propose a two-stage representation learning framework, B-FAIR, aimed at rectifying the unfairness caused by biased historical data in recommendation systems. The framework disentangles the context data into sensitive and non-sensitive components using a variational autoencoder and then applies a novel Balanced Fairness Objective (BFO) to remove bias in the observational data when training a recommendation model. The efficacy of B-FAIR is demonstrated through experiments on both synthetic and real-world benchmarks, showing improved performance over state-of-the-art algorithms

Fano-Rashba effect in thermoelectricity of a double quantum dot molecular junction

We examine the relation between the phase-coherent processes and spin-dependent thermoelectric effects in an Aharonov-Bohm (AB) interferometer with a Rashba quantum dot (QD) in each of its arm by using the Green's function formalism and equation of motion (EOM) technique. Due to the interplay between quantum destructive interference and Rashba spin-orbit interaction (RSOI) in each QD, an asymmetrical transmission node splits into two spin-dependent asymmetrical transmission nodes in the transmission spectrum and, as a consequence, results in the enhancement of the spin-dependent thermoelectric effects near the spin-dependent asymmetrical transmission nodes. We also examine the evolution of spin-dependent thermoelectric effects from a symmetrical parallel geometry to a configuration in series. It is found that the spin-dependent thermoelectric effects can be enhanced by controlling the dot-electrode coupling strength. The simple analytical expressions are also derived to support our numerical results

Sample entropy analysis of EEG signals via artificial neural networks to model patients' consciousness level based on anesthesiologists experience.

Electroencephalogram (EEG) signals, as it can express the human brain's activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA). Bispectral (BIS) index monitor is one of the famous and important indicators for anesthesiologists primarily using EEG signals when assessing the DOA. In this study, an attempt is made to build a new indicator using EEG signals to provide a more valuable reference to the DOA for clinical researchers. The EEG signals are collected from patients under anesthetic surgery which are filtered using multivariate empirical mode decomposition (MEMD) method and analyzed using sample entropy (SampEn) analysis. The calculated signals from SampEn are utilized to train an artificial neural network (ANN) model through using expert assessment of consciousness level (EACL) which is assessed by experienced anesthesiologists as the target to train, validate, and test the ANN. The results that are achieved using the proposed system are compared to BIS index. The proposed system results show that it is not only having similar characteristic to BIS index but also more close to experienced anesthesiologists which illustrates the consciousness level and reflects the DOA successfully.This research is supported by the Center forDynamical Biomarkers and Translational Medicine, National Central University, Taiwan, which is sponsored by Ministry of Science and Technology (Grant no. MOST103-2911-I-008-001). Also, it is supported by National Chung-Shan Institute of Science & Technology in Taiwan (Grant nos. CSIST-095-V301 and CSIST-095-V302)

High-energy scale revival and giant kink in the dispersion of a cuprate superconductor

In the present photoemission study of a cuprate superconductor Bi1.74Pb0.38Sr1.88CuO6+delta, we discovered a large scale dispersion of the lowest band, which unexpectedly follows the band structure calculation very well. The incoherent nature of the spectra suggests that the hopping-dominated dispersion occurs possibly with the assistance of local spin correlations. A giant kink in the dispersion is observed, and the complete self-energy containing all interaction information is extracted for a doped cuprate in the low energy region. These results recovered significant missing pieces in our current understanding of the electronic structure of cuprates.Comment: 4 pages, 3 figures, submitted to Phys. Rev. Lett. on May 21, 200

Molecular analysis of the microbial community structures in water-flooding petroleum reservoirs with different temperatures

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Proteomic approach to study the cytotoxicity of dioscin (saponin)

Dioscin, extracted from the root of Polygonatum zanlanscianense pamp, exhibits cytotoxicity towards human myeloblast leukemia HL-60 cells. Proteomic analysis revealed that the expression of mitochondrial associated proteins was substantially altered in HL-60 cells corresponding to the dioscin treatment, suggesting that mitochondria are the major cellular target of dioscin. Mitochondrial functional studies validated that mitochondrial apoptotic pathway was initiated by dioscin treatment. Changes in proteome other than mitochondrial related proteins implicate that other mechanisms were also involved in dioscin-induced apoptosis in HL-60 cells, including the activity impairment in protein synthesis, alterations of phosphatases in cell signaling, and deregulation of oxidative stress and cell proliferation. Current study of protein alterations in dioscin-treated HL-60 cells suggested that dioscin exerts cytotoxicity through multiple apoptosis-inducing pathways. © 2006 Wiley-VCH Verlag GmbH & Co. KGaA.postprin

Environmental factors and mortality risks associated influenza

BACKGROUND AND AIMS: The subtropical and tropical regions exhibit a distinct seasonality of influenza incidence from the temperate regions, and the mechanism behind it remains unclear. Environmental factors have been related to the transmission and survival of influenza viruses but no studies have ever explored the role of environmental factors on regulating severity of influenza infection. METHODS: We applied a Poisson regression model to the mortality data of two Asian metropolitan cities located at the subtropical zone, Guangzhou and Hong Kong. Interaction between …postprin

Disease burden of influenza in three tropic and sub-tropic cities in Asia

Powerpoint PresentationSession 2 - Disease burden and transmission dynamics of inter-pandemic influenzaThe impact of influenza on mortality in sub-tropical and tropical countries is poorly quantified. The obstacle is mainly from assessing the disease burden among irregular seasonality of influenza activities in the warm climates. In this study we applied statistical modeling methods to three metropolitan cities in East and Southeast Asia: Guangzhou, Hong Kong, and Singapore, all of which have standardized influenza surveillance networks for years 2004-2006. We applied the method of Generalized Additive Modeling (GAM) to evaluate the effect of influenza circulation in the community on all-cause mortality and on mortality with an underlying cause of cardio-respiratory diseases. The strength of GAM lies on its capability in adjusting for the seasonality of health outcomes in the investigation for their association with influenza activity, particularly in the subtropics and tropics. Our findings indicated that influenza was associated with 12.4 (95% confidence interval (CI): 1.2, 23.0), 13.9 (95% CI: 6.4, 20.9) and 8.7 (95% CI: 3.0, 13.9) deaths for all causes per 100,000 population in Guangzhou, Hong Kong, and Singapore, respectively. For the cardio-respiratory mortality, influenza was associated with 11.2 (95% CI: 2.4, 19.6), 9.1 (95% CI: 4.3, 13.6) and 5.5 (95% CI: 1.6, 9.4) deaths per 100,000 population in the three cites. These results showed that the disease burdens in the two subtropical cities Guangzhou and Hong Kong were similar and slightly higher than those in the tropical city, Singapore. In the future, a cross region study involving temperate, subtropical, and tropical climates could provide more information about the health effects of influenza in Asia.postprin