Background:
Drosophila gene expression pattern images document the spatiotemporal dynamics of gene expression during embryogenesis. A comparative analysis of these images could provide a fundamentally important way for studying the regulatory networks governing development. To facilitate pattern comparison and searching, groups of images in the Berkeley Drosophila Genome Project (BDGP) high-throughput study were annotated with a variable number of anatomical terms manually using a controlled vocabulary. Considering that the number of available images is rapidly increasing, it is imperative to design computational methods to automate this task.

Results:
We present a computational method to annotate gene expression pattern images automatically. The proposed method uses the bag-of-words scheme to utilize the existing information on pattern annotation and annotates images using a model that exploits correlations among terms. The proposed method can annotate images individually or in groups (e.g., according to the developmental stage). In addition, the proposed method can integrate information from different two-dimensional views of embryos. Results on embryonic patterns from BDGP data demonstrate that our method significantly outperforms other methods.

Conclusion:
The proposed bag-of-words scheme is effective in representing a set of annotations assigned to a group of images, and the model employed to annotate images successfully captures the correlations among different controlled vocabulary terms. The integration of existing annotation information from multiple embryonic views improves annotation performance.

Thermionic energy conversion, a process that allows direct transformation of thermal to electrical energy, presents a means of efficient electrical power generation as the hot and cold side of the corresponding heat engine are separated by a vacuum gap. Conversion efficiencies approaching those of the Carnot cycle are possible if material parameters of the active elements at the converter, i.e., electron emitter or cathode and collector or anode, are optimized for operation in the desired temperature range.

These parameters can be defined through the law of Richardson–Dushman that quantifies the ability of a material to release an electron current at a certain temperature as a function of the emission barrier or work function and the emission or Richardson constant. Engineering materials to defined parameter values presents the key challenge in constructing practical thermionic converters. The elevated temperature regime of operation presents a constraint that eliminates most semiconductors and identifies diamond, a wide band-gap semiconductor, as a suitable thermionic material through its unique material properties. For its surface, a configuration can be established, the negative electron affinity, that shifts the vacuum level below the conduction band minimum eliminating the surface barrier for electron emission.

In addition, its ability to accept impurities as donor states allows materials engineering to control the work function and the emission constant. Single-crystal diamond electrodes with nitrogen levels at 1.7 eV and phosphorus levels at 0.6 eV were prepared by plasma-enhanced chemical vapor deposition where the work function was controlled from 2.88 to 0.67 eV, one of the lowest thermionic work functions reported. This work function range was achieved through control of the doping concentration where a relation to the amount of band bending emerged. Upward band bending that contributed to the work function was attributed to surface states where lower doped homoepitaxial films exhibited a surface state density of ∼3 × 10[superscript 11] cm[superscript −2]. With these optimized doped diamond electrodes, highly efficient thermionic converters are feasible with a Schottky barrier at the diamond collector contact mitigated through operation at elevated temperatures.