The Z --> E photoisomerization and fluorescence quantum yields for the wild-type green fluorescence protein (GFP) chromophore (p-HBDI) and its meta- and para-amino analogues (m-ABDI and p-ABDI) in aprotic solvents (hexane, THF, and acetonitrile) and protic solvents (methanol and 10-20% H(2)O in THF) are reported. The dramatic decrease in the quantum yields on going from aprotic to protic solvents indicates the important role of solvent-solute hydrogen bonding in the nonradiative decay pathways. The enhanced fluorescence of m-ABDI is also discussed.

Three new tailor-made molecules (DPDCTB, DPDCPB, and DTDCPB) were strategically designed and convergently synthesized as donor materials for small-molecule organic solar cells. These compounds possess a donor-acceptor-acceptor molecular architecture, in which various electron-donating moieties are connected to an electron-withdrawing dicyanovinylene moiety through another electron-accepting 2,1,3-benzothiadiazole block. The molecular structures and crystal packings of DTDCPB and the previously reported DTDCTB were characterized by single-crystal X-ray crystallography. Photophysical and electrochemical properties as well as energy levels of this series of donor molecules were thoroughly investigated, affording clear structure-property relationships. By delicate manipulation of the trade-off between the photovoltage and the photocurrent via molecular structure engineering together with device optimizations, which included fine-tuning the layer thicknesses and the donor:acceptor blended ratio in the bulk heterojunction layer, vacuum-deposited hybrid planar-mixed heterojunction devices utilizing DTDCPB as the donor and C(70) as the acceptor showed the best performance with a power conversion efficiency (PCE) of 6.6 ± 0.2% (the highest PCE of 6.8%), along with an open-circuit voltage (V(oc)) of 0.93 ± 0.02 V, a short-circuit current density (J(sc)) of 13.48 ± 0.27 mA/cm(2), and a fill factor (FF) of 0.53 ± 0.02, under 1 sun (100 mW/cm(2)) AM 1.5G simulated solar illumination.

A novel donor-acceptor-acceptor (D-A-A) donor molecule, DTDCTB, in which an electron-donating ditolylaminothienyl moiety and an electron-withdrawing dicyanovinylene moiety are bridged by another electron-accepting 2,1,3-benzothiadiazole block, has been synthesized and characterized. A vacuum-deposited organic solar cell employing DTDCTB combined with the electron acceptor C(70) achieved a record-high power conversion efficiency (PCE) of 5.81%. The respectable PCE is attributed to the solar spectral response extending to the near-IR region and the ultracompact absorption dipole stacking of the DTDCTB thin film.

The unconstrained green fluorescence protein (GFP)-like chromophore m-DMABDI displays a high solvatofluorochromicity in aprotic solvents, but the fluorescence is quenched in protic solvents. According to the site-specific intramolecularly hydrogen-bonded analogs 1OH and 2OH, the hydrogen bonding to the carbonyl oxygen is more important than that to the imino nitrogen of the imidazolinone group in the fluorescence quenching.

This paper presents a new classifier called total margin-based adaptive fuzzy support vector machines (TAF-SVM) that deals with several problems that may occur in support vector machines (SVMs) when applied to the face recognition. The proposed TAF-SVM not only solves the overfitting problem resulted from the outlier with the approach of fuzzification of the penalty, but also corrects the skew of the optimal separating hyperplane due to the very imbalanced data sets by using different cost algorithm. In addition, by introducing the total margin algorithm to replace the conventional soft margin algorithm, a lower generalization error bound can be obtained. Those three functions are embodied into the traditional SVM so that the TAF-SVM is proposed and reformulated in both linear and nonlinear cases. By using two databases, the Chung Yuan Christian University (CYCU) multiview and the facial recognition technology (FERET) face databases, and using the kernel Fisher's discriminant analysis (KFDA) algorithm to extract discriminating face features, experimental results show that the proposed TAF-SVM is superior to SVM in terms of the face-recognition accuracy. The results also indicate that the proposed TAF-SVM can achieve smaller error variances than SVM over a number of tests such that better recognition stability can be obtained.

A D-A-A-type molecular donor (DTDCTP) featuring electron-accepting pyrimidine and dicyanovinylene blocks has been synthesized for vacuum-deposited planar-mixed heterojunction solar cells with C(70) as the acceptor, giving a power conversion efficiency as high as 6.4%.

We have synthesized a series of novel coplanar chromophores in which heteroarenes, namely, thiophene, benzothiophene, and carbazole, were fused to neighboring phenylene ring(s) through intramolecular annulation via sp(3)-hybridized carbon atoms bearing two p-tolyl groups as peripheral substituents. The molecular configurations of the pi-conjugated backbones were determined by X-ray crystallographic analysis; the heteroarene-fused molecular frameworks of these novel molecules exhibit nearly coplanar conformations. [structure: see text]

Major depressive disorder (MDD) has become a leading contributor to the global burden of disease; however, there are currently no reliable biological markers or physiological measurements for efficiently and effectively dissecting the heterogeneity of MDD. Here we propose a novel method based on scalp electroencephalography (EEG) signals and a robust spectral-spatial EEG feature extractor called kernel eigen-filter-bank common spatial pattern (KEFB-CSP). The KEFB-CSP first filters the multi-channel raw EEG signals into a set of frequency sub-bands covering the range from theta to gamma bands, then spatially transforms the EEG signals of each sub-band from the original sensor space to a new space where the new signals (i.e., CSPs) are optimal for the classification between MDD and healthy controls, and finally applies the kernel principal component analysis (kernel PCA) to transform the vector containing the CSPs from all frequency sub-bands to a lower-dimensional feature vector called KEFB-CSP. Twelve patients with MDD and twelve healthy controls participated in this study, and from each participant we collected 54 resting-state EEGs of 6 s length (5 min and 24 s in total). Our results show that the proposed KEFB-CSP outperforms other EEG features including the powers of EEG frequency bands, and fractal dimension, which had been widely applied in previous EEG-based depression detection studies. The results also reveal that the 8 electrodes from the temporal areas gave higher accuracies than other scalp areas. The KEFB-CSP was able to achieve an average EEG classification accuracy of 81.23% in single-trial analysis when only the 8-electrode EEGs of the temporal area and a support vector machine (SVM) classifier were used. We also designed a voting-based leave-one-participant-out procedure to test the participant-independent individual classification accuracy. The voting-based results show that the mean classification accuracy of about 80% can be achieved by the KEFP-CSP feature and the SVM classifier with only several trials, and this level of accuracy seems to become stable as more trials (i.e., <7 trials) are used. These findings therefore suggest that the proposed method has a great potential for developing an efficient (required only a few 6-s EEG signals from the 8 electrodes over the temporal) and effective (~80% classification accuracy) EEG-based brain-computer interface (BCI) system which may, in the future, help psychiatrists provide individualized and effective treatments for MDD patients.