A concise and effective three-step synthesis of 4a,8a-azaboranaphthalene (ABN) has been developed in gram scale. Electrophilic aromatic substitution reactions of ABN provide excellent functional-group-tolerant cross-coupling partners in various Pd-catalyzed cross-coupling reactions (e.g., Sonogashira, Suzuki-Miyaura, or Heck reaction). Photophysical, electrochemical, and DFT calculations all suggest a narrowed HOMO-LUMO gap with extended π-conjugation characters in the cross-coupled molecules. The ABN moiety as a new fluorophore has a distinct and selective fluorescence response toward Zn(II) and Cd(II) ions, demonstrating great potential for the ABN structural motif in fluorescent chemosensors.

One of the key procedures in color image compression is to extract its region of interests (ROIs) and evaluate different compression ratios. A new non-uniform color image compression algorithm with high efficiency is proposed in this paper by using a biology-motivated selective attention model for the effective extraction of ROIs in natural images. When the ROIs have been extracted and labeled in the image, the subsequent work is to encode the ROIs and other regions with different compression ratios via popular JPEG algorithm. Furthermore, experiment results and quantitative and qualitative analysis in the paper show perfect performance when comparing with other traditional color image compression approaches.

Realistic image rendition is to reproduce the human perception of natural scenes. Retinex is a classical algorithm that simultaneously provides high dynamic range compression contrast and color constancy of an image. In this paper, we discuss a design of a digital signal processor (DSP) implementation of the single scale monochromatic Retinex algorithm. The target processor is Texas Instruments TMS320DM642, a 32-bit fix point DSP which is clocked at 600 MHz. This DSP hardware platform designed is of powerful consumption and video image processing capability. We give an overview of the DSP hardware and software, and discuss some feasible optimizations to achieve a real-time version of the Retinex algorithm. In the end, the performance of the algorithm executing on DSP platform is shown.